About the Data Scientist Master's program developed in collaboration with IBM

IBM is the second-largest Predictive Analytics and Machine Learning solutions provider globally (source: The Forrester Wave report, September 2018). A joint partnership with Simplilearn and IBM introduces students to integrated blended learning, making them experts in Artificial Intelligence and Data Science. The Data Science course in collaboration with IBM will make students industry-ready for Artificial Intelligence and Data Science job roles. IBM is a leading cognitive solutions and cloud platform company, headquartered in Armonk, New York, offering a plethora of technology and consulting services. Each year, IBM invests $6 billion in research and development and has achieved five Nobel prizes, nine US National Medals of Technology, five US National Medals of Science, six Turing Awards, and 10 Inductions in the US Inventors Hall of Fame. What can I expect from these Data Science courses developed in collaboration with IBM? Upon completion of this Data Scientist online Master's program, you will receive the certificates from IBM(for IBM courses) and Simplilearn for the courses in the learning path. These certificates will testify to your skills as an expert in Data Science. You will also receive the following: Access to IBM Cloud Lite account Industry-recognized Data Scientist Master's certificate

What are the learning objectives?

Data Scientist is one of the hottest professions. IBM predicts the demand for Data Scientists will rise by 28% by 2020. Data Scientist Master’s program co-developed with IBM encourages you to master skills including statistics, hypothesis testing, data mining, clustering, decision trees, linear and logistic regression, data wrangling, data visualization, regression models, Hadoop, Spark, PROC SQL, SAS Macros, recommendation engine, supervised, and unsupervised learning and more. This Data Scientist Master’s program covers extensive Data Science training, combining online instructor-led classes and self-paced learning co-developed with IBM. The program concludes with a capstone project designed to reinforce the learning by building a real industry product encompassing all the key aspects learned throughout the program. The skills focused on in this program will help prepare you for the role of a Data Scientist.

Why be a Data Scientist?

A Data scientist is the top ranking professional in any analytics organization. Glassdoor ranks Data Scientists first in the 25 Best Jobs for 2019. In today’s market, Data Scientists are scarce and in demand. As a Data Scientist, you are required to understand the business problem, design a data analysis strategy, collect and format the required data, apply algorithms or techniques using the correct tools, and make recommendations backed by data.

What important Data Science skills you will learn with this Master’s program?

Gain an in-depth understanding of data structure and data manipulation Understand and use linear and non-linear regression models and classification techniques for data analysis Obtain an in-depth understanding of supervised and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave Gain expertise in mathematical computing using the NumPy and Scikit-Learn packages Understand the different components of the Hadoop ecosystem Learn to work with HBase, its architecture, and data storage, learning the difference between HBase and RDBMS, and use Hive and Impala for partitioning Understand MapReduce and its characteristics, plus learn how to ingest data using Sqoop and Flume Master the concepts of recommendation engine and time series modeling and gain practical mastery over principles, algorithms, and applications of machine learning Learn to analyze data using Tableau and become proficient in building interactive dashboards

What Data Science projects are included in this Master's program?

This Data Scientist Master's program includes 15+ real-life, industry-based projects on different domains to help you master concepts of Data Science and Big Data. A few of the projects that you will be working on are mentioned below: Capstone Project: Description: You will go through dedicated mentor classes in order to create a high-quality industry project, solving a real-world problem leveraging the skills and technologies learned throughout the program. The capstone project will cover all the key aspects of data extraction, cleaning, and visualization to model building and tuning. You also get the option of choosing the domain/industry dataset you want to work on from the options available. After successful submission of the project, you will be awarded a capstone certificate that can be showcased to potential employers as a testament to your learning. Project 1: Products rating prediction for Amazon Domain: E-commerce Amazon, one of the leading US-based e-commerce companies, recommends products within the same category to customers based on their activity and reviews on other similar products. Amazon would like to improve this recommendation engine by predicting ratings for the non-rated products and add them to recommendations accordingly. Project 2: Improving customer experience for Comcast Domain: Telecom Description: Comcast, one of the leading US-based global telecommunication companies wants to improve customer experience by identifying and acting on problem areas that lower customer satisfaction if any. The company is also looking for key recommendations that can be implemented to deliver the best customer experience. Project 3: Attrition Analysis for IBM Domain: Workforce Analytics Description: IBM, one of the leading US-based IT companies, would like to identify the factors that influence the attrition of employees. Based on the parameters identified, the company would also like to build a logistics regression model that can help predict if an employee will churn or not. Project 4: Predict accurate sales for 45 stores of Walmart, one of the leading US-based leading retail stores, considering the impact of promotional markdown events. Check if macroeconomic factors like CPI, unemployment rate, etc. have an impact on sales. Domain: Retail Description: Walmart runs several promotional markdown events throughout the year. The markdowns precede prominent holidays, such as the Super Bowl, Labour Day, Thanksgiving, and Christmas. The weeks including these holidays are weighted five times higher in valuation than non-holiday weeks. The business is facing a challenge due to unforeseen demand, resulting in stocks running out at times due to inaccurate demand estimation. The macroeconomic factors like CPI, Unemployment Index, etc. also play an important role in predicting the demand, but the business hasn’t been able to leverage these factors yet. As a part of this project, create a model to highlight the effects of markdowns on holiday weeks. Project 5: Learn how leading Healthcare industry leaders make use of Data Science to leverage their business. Domain: HealthCare Description: Predictive analytics can be used in healthcare to mediate hospital readmissions. In healthcare and other industries, predictors are most useful when they can be brought into action. However, historical and real-time data alone are worthless without intervention. More importantly, to judge the efficiency and value of forecasting a trend and ultimately changing behavior, both the predictor and the intervention must be integrated back into the same system and workflow where the trend originally occurred. Project 6: Understand how Insurance leaders like Berkshire Hathaway, AIG, AXA, etc. make use of Data Science by working on a real-life project based on Insurance. Domain: Insurance Description: The use of predictive analytics has increased greatly in insurance businesses, especially for the biggest companies, according to the 2013 Insurance Predictive Modeling Survey. While the survey showed an increase in predictive modeling throughout the industry, all the respondents from companies that write over $1 billion in personal insurance employ predictive modeling, compared to 69% of companies with less than that amount of premium. Project 7: See how banks like Citigroup, Bank of America, ICICI, HDFC, etc. make use of Data Science to stay ahead of the competition. Domain: Banking Description: A Portuguese banking institution ran a marketing campaign to convince potential customers to invest in a bank term deposit. Its marketing campaigns were conducted through phone calls, and sometimes the same customer was contacted more than once. Your job is to analyze the data collected from the marketing campaign. Project 8: Learn how Stock Markets, such as NASDAQ, NSE, and BSE leverage Data Science and Analytics to arrive at consumable data from complex datasets. Domain: Stock Market Description: You need to import data using Yahoo data reader of the following companies: Yahoo, Apple, Amazon, Microsoft, and Google. Perform fundamental analytics including plotting closing price, plotting stock trade by volume, performing daily return analysis, and using pair plot to show the correlation between all the stocks. Project 9: See how Data Science is used in the field of engineering by taking up this case study of MovieLens Dataset Analysis. Domain: Engineering Description: The GroupLens Research Project is a research group in the Department of Computer Science and Engineering at the University of Minnesota. The researchers of this group are involved in many research projects related to the fields of information filtering, collaborative filtering, and recommender systems. Project 10: Understand how leading retail companies like Walmart, Amazon, Target, etc. make use of Data Science to analyze and optimize their product placements and inventory. Domain: Retail Description: Analytics is used in optimizing product placements on shelves or optimization of inventory to be kept in the warehouses using industry examples. Through this project, participants learn the daily cycle of product optimization from the shelves to the warehouse. This gives them insights into regular occurrences in the retail sector.

Who should take this Data Scientist Master’s program?

The Data Science role requires an amalgam of experience, data science knowledge, and correct tools and technologies. It is a solid career choice for both new and experienced professionals. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue the Data Science course, including: IT Professionals Analytics Managers Business Analysts Banking and Finance Professionals Marketing Managers Supply Chain Network Managers Beginners or Recent Graduates in Bachelors or Master’s Degree

What are the prerequisites for this Data Science training?

Professionals wishing to succeed in this Data Science course should have: Basic knowledge of statistics Basic understanding of any programming language

What type of jobs will I be suited for after completing this Data Science course?

Data Science course, you will have the skills that will help you land your dream job in Data Science. Jobs that are ideal for data science-trained professionals include: Data Analyst Data Scientist Analytics Manager/Lead Machine Learning Engineer Statistical Programming Specialist

What is Data Science course?

Data Science is a broad field and you need to learn about so many concepts if you are a beginner. A Data Science course is a training program of around six to twelve months, often taken by industry experts to help candidates build a strong foundation in the field. Apart from the theoretical material, an online data science course includes virtual labs, industry projects, interactive quizzes, and practice tests which can give you enhanced learning experience.

Will this course help me to learn Data Science from scratch?

Professionals who do not have any prior knowledge of the field can easily begin with this Data Scientist Master’s program as you’ll gain a thorough knowledge of the basic concepts as well.

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DevOps Training Course in Delhi

Name: Data Scientist
Item: Data Scientist
Rating: 5

(4.9)

859 Ratings 1654 Learners

Intensive Classroom & instructor led online sessions
Covers Basic Intermediate & Advanced Level
60+ hours of handson assignments & Capstone Projects
100% Placement Assurance
Curriculum Reviewed by Industry Experts
Learn Puppet, Git, Jenkins, Maven, Docker, Ansible, Kubernetes, Nagios, Terraform and DevSecOps etc.

Aws DevOps - The Big Picture
Linux - Fundamentals & Cloud
Git & GitHub - Version
Maven - Build Automation
Tomcat & Nginx - Deployments
Kubernetes & Microservices
Advanced Shell scripting

Key Features

Instructor-led Training

Self-paced Videos

Project Work & Exercises

Exhaustive Hands-on Sessions

24 x 7 Lifetime Support & Access

Certification and Job Assistance

About The Program

CI, CD and Aws DevOps have taken over the software development world by storm. Most companies today realize that the practices of continuous integration (CI) and continuous delivery (CD) will yield tremendous benefits like increased business revenue and faster time-to-market. The demand for these skills has been steadily rising over the last few years.

There are a plethora of tools available in the CI/CD/Aws DevOps landscape today. Implementing continuous integration, continuous delivery and continuous deployment with these tools and frameworks can help us immensely in modernizing our software development lifecycle. It catches us bugs early and increases the quality of our software products. This, in turn, reduces the overall cost for software development in startups and enterprise alike.

DeepNeuron Aws DevOps course has been designed keeping in mind the latest industry needs. You will be trained on the following skillsets which have been curated based on job descriptions posted by companies looking for Aws DevOps Engineers. In this Aws DevOps online course, you will learn the following aspects:

But before getting into tools and frameworks, it is important that you get a holistic picture of CI / CD and Aws DevOps. For this, you need to understand where we started from - the old school traditional software development cycle. We will pick holes in the old model, identify pain points and learn how CI / CD and Aws DevOps evolved, one step at a time. Once you build a rock solid foundation using this course, you can move on to more specific tool oriented courses.

If you are thinking about moving on to CI/CD/Aws DevOps from your old school software development model, this course is for you. Well illustrated with animations to help you grasp a clear understanding of the underlying principles. Once you complete this course, you can take on bigger challenges related to implementation. The demand for professionals who have experience with CI/CD/Aws DevOps has been growing steadily over the last few years. The salaries for these skills have gone through the roof and are only bound to go up as the demand for these skills increases. Professionals with CI / CD / Aws DevOps skill set can demand as much as $150K as their yearly compensation as per latest US job and salary surveys. And this is where you start!

In-depth knowledge of Aws DevOps methodology

Implementing Software Version Control

Containerizing Code on production using Docke

Creating CI/CD Pipelines using Jenkins

Configuration Management using Puppet and Ansible

Automating build and test using Selenium and Maven

Container Orchestration using Kubernetes

Performance Tuning and Monitoring using Nagios

These Aws DevOps classes can be taken up by:

IT Professionals

Software Testers

System Admins

Solution Architects

Security Engineers

Application Developers

Integration Specialists

Basic knowledge of Linux or scripting is good to have. For this, we provide you with a free Linux self-paced course to help speed up your learning.

Prior IT experience would be necessary for learning this technology.

All our practical sessions, case studies, and projects will be performed on the AWS Cloud. We will help you set up your AWS Free Tier account once you enroll for the Aws DevOps course. We will also provide you VMs, which will help you practice even when you’re offline!

The Aws DevOps industry is expected to grow six times higher by the year 2022, according to Gartner.

The average annual salary of a Aws DevOps engineer in the US is $ 136,500, and in India it is approximately INR 666,232 (PayScale).

Additionally, Aws DevOps and Cloud jobs are going to be among the highest paying jobs in the coming years, according to Forbes.

A Aws DevOps Architect is the backbone of any organization’s technical team.

Programming Languages,Tools & Packages

Aws DevOps Course Modules

AWS provides services that help you practice DevOps at your company and that are built first for use with AWS. These tools automate manual tasks, help teams manage complex environments at scale, and keep engineers in control of the high velocity that is enabled by DevOps.

Our DevOps online course is purely practical-based with hands-on tutoring with Doubt clarification sessions.

We give full curriculum coverage from basics to advanced level.

Our curriculum is adaptive to day-to-day trending concepts in the domain.

Our trainers are cherry-picked industry experts working for top MNCs across the globe.

You will master DevOps with module-based hands-on sessions & live projects.
Corporate Readiness - Mock Interviews, Interview Question discussion, etc.

Wiculty's Course Completion Certificate is recognized across the industry.

Concept planting: Any topic you learn here will have strong concept demonstration, Practicals, Projects, Best practices, Interview questions, and real-time use cases - pitching an effective learning experience

History of UNIX/LINUX
Features and Benefits of UNIX/LINUX
Different flavors of UNIX/LINUX
Difference between UNIX, DOS, Windows and LINUX
Architecture of UNIX

Commands: pwd, ls, cd, cat, cp, mv, mkdir, rm, rmdir, touch, locate, find, grep, sudo, df, du, head, tail, diff, tar, chmod, chown, jobs, kill, ping, ssh, useradd, sshpass, scp, ifconfig, apt-get, curl, wget, uname, top, history, man, echo, zip, unzip, hostname, useradd, userdel, man, help, uname, apt-get, chmod, who, whoami, cal, date, exit.

Job oriented: Hands-On preparation

Concepts & Practicals

Creating Virtual Machine using Oracle Virtualbox
AWS free-tier account creation
EC2 Instance creation and setup
Accessing EC2 Instance using .pem & ppk keys
SSH command

Job oriented: Hands-On preparation

Real-time Use-cases
Interview Questions discussion

Concepts & Practicals

Ordinary Files
Directory Files
Device Files
The Structure of UNIX File system

Job oriented: Hands-On preparation

Real-time Use-cases & Applying the commands to solve different problems
Interview Questions discussion

Concepts & Practicals

Editing- Insert, Append, substitute, open new line, replace

Navigating - Cursor movement shortcuts
Revisiting Editing - cut, copy, paste, undo, redo

Searching - settings, search in current and multiple files

Creating a file, view read-only, edit file
Job oriented: Hands-On preparation
Applying all the vim shortcuts and practice on data files

Concepts & Practicals

Editing- Insert, Append, substitute, open new line, replace
Navigating - Cursor movement shortcuts
Revisiting Editing - cut, copy, paste, undo, redo
Searching - settings, search in current and multiple files
Creating a file, view read-only, edit file
Job oriented: Hands-On preparation
Applying all the vim shortcuts and practice on data files

Concepts & Practicals

Redirecting Output
Redirecting Input
STDIN, STDOUT, STDERR
Commands: cat, touch, rm, cp, mv, ln, wc, mkdir, cd, rmdir, rm, ls, ls with options, find, locate, chmod, chown
Mounting directories (mount, unmount)
File & Directory Permissions (chmod, chown)
Job oriented: Hands-On preparation

Real-time Use-cases & Applying the commands to solve different problems
Interview Questions discussion

Concepts & Practicals

Hard Link
Soft link or Symbolic Link
Unlink
Filters: tr, tee, sed, pg, more, less, head, tail, paste, cut, sort, grep, egrep
Usage of piping
Archive: gzip, gunzip, tar, zip, unzip with different options
Disk usage, File/Dir size (df, du)

Job oriented: Hands-On preparation

Real-time Use-cases & Applying the commands to solve different problems
Interview Questions discussion

Concepts & Practicals

Foreground jobs
Background jobs
Killing jobs
Nohup
Process hierarchy (ps, kill)
Configuring Crontab

Job oriented: Hands-On preparation

Real-time Use-cases & Applying the commands to solve different problems
Interview Questions discussion

Concepts & Practicals
SSH - Configurations & Connecting to remote machines
SCP - copying the files/directories to remote
sshpass
Curl
Ssh-keygen

Job oriented: Hands-On preparation

Real-time Use-cases & Applying the commands to solve different problems
Interview Questions discussion

Concepts & Practicals
Types of accounts in Unix system
Create, Modify, Delete a Group
Create, Delete, Modify an User Account
CPU, Memory, Disk space Check
Performance tools (netstat, uptime, time, top)
System Logging

Job oriented: Hands-On preparation
Real-time Use-cases & Applying the commands to solve different problems
Interview Questions discussion

Concepts & Practicals
Introduction to version control systems (VCS)
Different version control systems in the market
Evolution of VCS
Roles and goals of VCS in Source code management & DevOps
Principles & features of Version Control Systems
What is Git & Github? Differences!
Roles and Responsibilities of DevOps Engineer in Git & Github
Job oriented: Hands-On preparation
Creating an end-to-end flow-chart fitting Git in DevOps echo system
Note: As It's just an introduction, you see more hands-on in upcoming Chapters

Concepts & Practicals
Git Basics & Architecture
Git's unique features in Source code management
End-to-End Git Work-flow. A bird's eye view
Git Vs SVN Vs Other commercial VCS
Git Command Line & GUI
On-premise Vs Hosted Git Solutions
Overview of GitHub, GitLab, Bitbucket. etc..
Job oriented: Hands-On preparation
Creating Git Architecture diagram to answer in interviews
Applying Git commands and perform end-to-end hands-on
Exploring GitHub and it's UI features
Note: As It's just an introduction, you see more hands-on in up coming Chapters

Concepts & Practicals
Test your knowledge! Git Jargons. How much you can talk?
Git Installation, Uninstallation, Upgradation on Linux
Setting up Mandatory configurations & best practices
'$git config' command to setup User, Email, Editor and Credentials
What is Source, Stage and Local repository.
Git Revision Structure – SHA, User, Email, Commit Message and other metadata
Git internals. How Git generates SHA value? What is this checksum code & data integrity all about?
Significance of Staging Index. Skipping the staging. Best practices.
Job oriented: Hands-On preparation
Setting up Remote repository on GitHub from scratch
End-to-End git work-flow execution with commands
Commit your first change to Remote repository, Consciously!
$Commands: ‘git add’, ‘git commit’, ‘git push’ with options

Concepts & Practicals
Git command line with most frequently used options in real-time
# Check the history of a file
$ git log –author
$ git log --grep
$ git log –since
$ git log –until
$ git log –oneline
$ git log --grep , etc.
# How do you get diff of your changes?
$ git diff
$ git diff --staged
$ git diff sha..sha
# Removing a file in Git
$ git rm
- Is deletion permanent? Best practices.
- Resurrect a deleted file
# Renaming a file in Git
$ git mv command
- Verify history after file rename
# Show more details about a change
$ git show
# Undoing the changes
- Revert a change from Source Area
- Revert a change from staging area
- Revert a committed change
$ Git pull & fetch commands
- Difference between pull and fetch
- Difference between clone and pull
- Pull and Fetch best practices
Job oriented: Hands-On preparation
Practice all above commands with real-time use cases. In what case you apply?
Can you explain where you have used all these commands in your project from interview perspective?

Concepts & Practicals
What is a branch? When and Why do we create a new branch
Importance of master branch & stable code
Branching Strategies/Models – Pros and Cons
Switching branches for parallel development
Merging from one branch to another. Best practices
Job oriented: Hands-On preparation
Creating a new branch and making it public
Explain the branching model that you followed in your project for different releases.
Merging & Conflict resolution. Practice a complete cycle

Concepts & Practicals
Build and Deployment automation End-to-End Workflow
Roles and Responsibilities of DevOps Engineer in Software Build & Deployment
Introduction to Maven build tool
Maven Vs ANT(Key Features of Maven Over ANT)
Feel the pain of source code manual compilation with manual example
Necessity of compilation and transforming source code into binaries/executables
Artifact, Binaries, Executables, object code definition - Get terminology
Job oriented: Hands-On preparation
Explain complete flow of software development, build and test process
Flow chart for the same

Concepts & Practicals
Maven Installation and Prerequisites, Downloading Maven and JDK
Setting up JAVA_HOME, M2_HOME and PATH ENV variables
Discussion about $USER_HOME/.bashrc file and Installation of any tool in Linux
Java build process. Packaging sequence (.Class, .Jar, .War, .Ear , etc.)
TEST YOUR KNOWLEDGE BEFORE DEEP DIVE:
What is compilation & why we compile the source code
Packaging sequence for Java application
What is Build
What is Deployment
Different Environments in Software development
Development, QA, Ops & DevOps teams Interaction and Collaboration
Job oriented: Hands-On preparation
Setting up Maven in your practice Linux machine
Setting up environment variables for any tool installation on Linux

Concepts & Practicals
Creating a project using Maven
Maven's convention over configuration feature
Understanding Project source structure
Understanding Test Driven Development (TDD) approach
Understanding Junit unit testing framework
Overview of Software development & other testing methodologies
Software Development and Testing Best practices
Job oriented: Hands-On preparation
Creating a first project in practice Linux machine
Explore project structure, main application and unit testing source

Concepts & Practicals
Building your first project
$ mvn install command & deep discussion about maven life cycle phases
Understanding build output, test results, class files, packages etc.
Verifying built artefacts, naming convention and m2 local repository
Dependency Management: What is code dependency-Maven's automatic dependency resolution feature
Direct and Transitive dependencies-Defining dependencies in pom file
Maven binary repositories-Local, Private and Central repository
Job oriented: Hands-On preparation
Build the project that you have created
Witness the build output and artefacts
Explain Maven's internal automation process

Concepts & Practicals
Build Types - hands-on
Complete build/Clean build/Full build
Nightly build
Daily build
bugfix build
adhoc/unplanned/emergency builds
Job oriented: Hands-On preparation
Execution of all build types with hands-on for GamutKart project
Maven plugins, Skipping Test compilation, run and execution of tests when required
- $ mvn install -DskipTests
- $ mvn install -Dmaven.test.skip=true
- $ mvn surefire:test
Creating project for web application. Building the war file

Concepts & Practicals
Understanding various Environments Usage: DEV, QA, SIT, UAT, Performance, STAGE, PROD. etc..
Deployment promotion methodologies from one environment to another environment
Application servers and web servers - Comparison
Tomcat startup scripts, deployment path, port configurations etc.
Exploring WAR / EAR files and its resources
Deployment best practices & roll back process
Job oriented: Hands-On preparation
Project-1: Automate complete build and deployment process for basic application using Maven and Shell scripts
Project-2: Building and deploying GamutKart project - Real-time project in your machine
Making you comfortable to work with Dev, QA & Ops teams in Agile environment understanding SLA's and support

Concepts & Practicals
Web application architecture, Client/Server model.
Application Server Vs Web server. When do you use what?
Static code Vs Application code deployments.

Concepts & Practicals
Tomcat Installation and Server launcher scripts
Tomcat Architecture & Components overview
Application deployment path & deployments
Understanding application and tomcat logs
SSL configuration in Tomcat
Job oriented: Hands-On preparation
Installation of JDK and configuring JAVA_HOME Environment Variable

Concepts & Practicals
Introduction to Agile Development
Definition of Continuous Integration (CI), Continuous Delivery (CD), Continuous Deployment (CD)
Difference between CI and CD
End-to-End CI & CD Pipeline concepts
Job oriented: Hands-On preparation
Explain How CI/CD helps to speed up Dev, QA and Ops process - Time To Market
Explain What is CI/CD & It's Architecture

Concepts & Practicals
Jenkins Installation and Configuration in Production
Tomcat and JDK installation. Setting up environment variables.
Exploring Jenkins Dashboard UI
Git, Maven and & Build tools Installations & integration
Different types of Jenkins Jobs. Freestyle, Pipeline, multi-configuration projects
Creating Jenkins Pipeline jobs and understanding all project options
Configuring automated Builds for WAR package creation
Job oriented: Hands-On preparation
Setting up Jenkins in your machine
Create first Jenkins job and automate builds for Gamut Kart (Our own Project)
Integrating source code management tools and polling VCS for to achieve C.I/C.D

Concepts & Practicals
Jenkins global configurations and administration settings
Build tools configuration in Manage Jenkins
Jenkins job build steps, triggers and post build actions
Setting up System notifications for users
Email configuration for sending CI/CD notifications
Jenkins backup mechanisms and restoration policies
Jenkins migration and upgradation
Setting up Security for Jenkins
Matrix based and Project based security
Jenkins authorizations to Dev, QA and other stakeholders. Best Practices
Job oriented: Hands-On preparation
Installation of thin backup plugin and configuring auto backups
Integrating Jenkins with LDAP for Authentication
Setting up authorization policies using matrix-based security
Creating Users and setting up authorization policies

What is a pipeline?
Advantages of build pipelines
Creating pipeline projects using GUI
Manual/GUI pipeline Vs scripted pipeline
Groovy scripts DSL and syntax
Creating Parameterized build jobs
Job oriented: Hands-On preparation
Write deployment scripts for different environments
Writing pipeline script:Jenkinsfile in declarative Groovy
Deployments to QA, SIT, UAT, etc environments using a single Jenkins job

Concepts & Practicals
Introduction to Plugins. What is a plugin?
Plugins Installation, Un-installation and upgrade
Different ways of plugin installation and management
Finding suitable plugins and interpreting plugins documentation for real-time scenarios
Use cases and applying Jenkins CLI for real-time scenarios
Explore Jenkins CLI options
Job oriented: Hands-On preparation
Most Frequently used plugins in real-time
Triggering build jobs from command line
Cleaning up builds runs using CLI

Concepts & Practicals
When do we implement distributed builds?
Setting master and slave nodes. Best practices
Running builds in parallel on distributed environment
Setting up and using SSH agents, cloud agents
Load balancing and fine tuning builds and deployments using master and slave
Job oriented: Hands-On preparation
Configuring master and slave mechanism
Configuring slave nodes and adding to master
Developing build and deployment automation for Gamut Kart (Our own project) on Master & Slave nodes

Concepts & Practicals
Basics of Virtualization
Difference between Virtual machine (VM), Physical machine and Docker container
What is containerization?
What is Docker? Why Docker and it's features. Who can use it?
Job oriented: Hands-On preparation
Virtual machine and Docker usage in real-time and DevOps world

Concepts & Practicals
Docker supported platforms
Docker prerequisites in production and commands to verify the same
Docker Installation & Uninstallation in production
Configuring Docker to be executed without sudo
Job oriented: Hands-On preparation
Install Docker in your lab machine from scratch

Concepts & Practicals
Creating first container
Cgroup & Namespace Kernel features for containers
Root file system, networking and processes isolation.
Docker image concepts. Shipping the application code with dependencies
Difference between Docker Image and Container
Creating any flavor of Linux containers on any linux host
Creating Linux containers on Windows. Concepts involved

Job oriented: Hands-On preparation
Creating container with different options
Installation of frequently used Linux commands (ssh, net-tools, vim ..etc. )
Inspecting the new container (hostname, IP, hosts file, processes, n/w capabilities ..etc.)
SSH installation in containers and enabling SSH for root

Concepts & Practicals
Shutdown Docker container
Listing all containers in host
Listing only running containers
Listing last few number of containers
Inspecting docker container information
Listing last created container
Creating a container with our own name
Renaming a container
Deleting one, all, stopped and running containers
Starting, stopping and restarting containers from host
Attaching to a running container
Keyboard shortcuts
Inspecting container processes from host
Stopping the container gracefully and forcibly
Find more about a container. Understanding container inspect JSON format
Creating and Pushing a running container in daemon mode
Creating demonized containers
Pushing container in sleep mode
Job oriented: Hands-On preparation
For all above commands, discussion about different use cases
When do we use a particular command
Execute all command in your lab machine in practical ways

Concepts & Practicals
Verifying resource utilization and usage statistics - stats command
Allocating Memory
Allocating CPU
Allocating Disk space
Updating computing constraints on a running container

Job oriented: Hands-On preparation
Discussion about when to change compute parameters
Pros & Cons of allocating dedicated memory manually
Execute all commands on your lab machine

Concepts & Practicals
Docker Volume creation
Inspecting Volumes
Mounting Docker volume to containers
Read-only volume

Job oriented: Hands-On preparation
Applying Volumes for Persistent data - Real-time use cases
Removing Volumes and all unused Volumes
Use-case discussion, Volumes to store user data in e-commerce application

Concepts & Practicals
Understand more about Docker images - real-time use cases in DevOps
Advantages of Docker images in application deployments
Docker Image creation techniques
Dockerfile instructions and usage
Solving 'Works in my machine problem' with Docker Images
Restoring environments with Docker images
Auto scaling environments using Images
Setting up dev environments with images. Docker Advantage!
Creating and setting up account in Docker-hub
Job oriented: Hands-On preparation
Writing Dockerfile for to create image for containerizing Gamutkart application
Most frequently used and helpful images walk-through
Implementing Self-service deployment models.
Setting up nginx for web application
Project:1 - creating custom Docker image for Nginx web application
Project:2 - Creating custom Docker image for our own Gamutkart e-commerce web application

Concepts & Practicals
Creating disposable environments using Docker images
Integrating Docker with Jenkins CI/CD Pipeline
Writing deployment scripts for provisioning environments with images

Job oriented: Hands-On preparation
Scaling up environments instantly with docker images.
Writing shell scripts for environment creation and management

Concepts & Practicals
Project-1: - Web Application Deployment & Hosting using Docker Images
Create docker image with Web application code, Nginx and other prerequisites and dependencies
Creating auto environments with shell scripts and Docker images

Project-2: - Gamutkart web application deployment & Environment setup automation
Building Gamutkart Application
Creating Docker image for Gamutkart application with prerequisites such as JDK, Tomcat & other configurations
Creating environments automatically usgin shell script and launch Gamutkart e-commerce application

Concepts & Practicals
What is Kubernetes? History of Kubernetes
Kubernetes Architecture & Building Blocks
Docker Vs Kubernetes (Complementary technologies)
Application deployment challenges. Why Container Orchestration tools?
Kubernetes as Data Centre OS

Job oriented: Hands-On preparation
Use case - Google Challenges & Experiences of running billions of containers
Container Orchestration Capabilities in real-time: Autoscaling, Zero Downtime Release, Rollback, Self-healing, Rolling Updates ..etc.

Concepts & Practicals
Installing Kubernetes using Kubeadm
Production Kubernetes cluster setup with multiple nodes
Kubernetes Services, Deep-dive
Master/Controle Plane Server
Worker Nodes
Kube-API Server
Kube-Controller
Kube-Scheduler,
Cluster-Store/etcd DB
Kubelet
Kube-Proxy
Kubectl, Container runtime
Job oriented: Hands-On preparation
Setting up 2-node Kubernetes cluster in Google cloud platform
Kubernetes cluster management practices

Concepts & Practicals
Monolithic Vs Microservice Architecture
Development, Build, Deployment & stability challenges in Monolith
From Monolith to Microservices - Project ideation
The Docker & Kubernetes role in Microservices

Job oriented: Hands-On preparation
Discussion - How Microservice concept helps deployment automation and environment stability.

Concepts & Practicals
What is POD? POD Vs Container
Single & Multi Container PODs & Use cases
POD - Horizontal scaling
Creating Pods - Writing Yaml files
Deploying Pods & to Run the application on Kubernetes
Pod life-cycle management commands

Job oriented: Hands-On preparation
Project:1 - Create 10 pods in Kubernetes cluster and run Nginx application
Project:2 - Create 10 pods in Kubernetes cluster and run GamutKart web application

Concepts & Practicals
Application Autoscaling, Self-healing, Rollbacks & Rolling Updates with Zero downtime
Kubernetes declarative Model - Desired state & Current state
ReplicaSet objects and create Deployment object - Writing Yaml files
Kubernetes deployment management commands
Inspecting PODs and application instances

Job oriented: Hands-On preparation
Project:1 - Implement Self-healing & Auto-scaling for Nginx application
Project:2 - Implement Self-healing & Auto-scaling for GamutKart web application

Concepts & Practicals
Create a Service object that exposes an external IP address - Writing Yaml files
Google Cloud basics. Creating compute instances in Google Cloud Platform (GCP)
Setting up Firewall rules and ports
Setting up NodePort Load balancer

Job oriented: Hands-On preparation
Project:1 - Create 10 POD instances, Setup the Load-balancer for Nginx application & make it accessible by the end-user.
Project:2 - Create 10 POD instances, Setup the Load-balancer for GamutKart web application & make it accessible by the end-user.

What is a configuration Management tool. What is Ansible?
How Ansible Works
What is Infrastructure as a code
About Idempotency behaviour
About some important Ansible Terminology
Job oriented: Hands-On preparation
Creating an end-to-end flow-chart fitting Ansible in DevOps echo system
Note: As It's just an introduction, you see more hands-on in upcoming Chapters

Concepts & Practicals
Ansible Architecture
Pre-Requisites for controller Node
Test Environment Setup
Installation and configuration
Ansible Configuration file
Pre-Requisites for Managed Node
Ansible Inventory
Ansible Communication
Communication checks with password Authentication
Communication with key-Based Authentication
Ansible Architecture
Overriding the Default HOSTS File
The Default System Ansible.Cfg File
Overriding the Default Roles Path
Job oriented: Hands-On preparation
Creating Ansible Architecture diagram & important interveiw questions
Applying Basic commands and perform end-to-end hands-on
Setup Ansible in your practice machine and get ready with required configurations

Concepts & Practicals
Why use ad-hoc commands? Syntax of ad-hoc commands
Use cases for ad-hoc tasks
Copying and Executing Modules:
Running first Ansible commands
Rebooting servers
Managing files,Managing packages
Managing users and groups
Managing services
Gathering facts
Job oriented: Hands-On preparation
command module, copy module,user module, gathering facts, shell module
Adhoc Commands To:
Login 'all' and execute python with json lib.
login 'hostname' and execute python with json lib.
Display facts from all hosts and store them indexed by hostname at /tmp/facts
List all the files and folders using command module
Cat a file using command module
Copy file from local to remote using copy module
Install package using apt module
Uninstall package using apt module
Create user ansi and set the password in all target servers using user module
Remove user ansi in all target servers using user module

Concepts & Practicals
what is configuration, deployment, and orchestration
YAML Structure, Playbook structure
Ansible playbooks - quick start
Playbook syntax checks
Variables in Ansible
Ansible Sections - target, tasks, handlers
Patterns: targeting hosts and groups
Defining Variables in Ansible Code, Use Cases
Debug the console logs
Job oriented: Hands-On preparation
Write a playbook to install package “tree” and check the version in remote/target servers
Write a playbook to copy a file to remote servers from Management server
Ansible Sections, Target section,tasks Section – Install Apache2 Package
Defining variables in “vars.yml” file and call the file in Playbook “4_callVarsFile.yml”
Debug- date/time stamp and debug

Concepts & Practicals
What is Conditionals in Ansible
What are Loops in Ansible
Handlers in Ansible
Ansible Vaults- Introduction and Importance of vaults in Ansible
Vault - commands and usage in playbooks
Job oriented: Hands-On preparation
Loops: with_items -Create list of users in a target/remote servers
Delete a list of users in a target/remote servers using loops concept
Install list of packages using loops concepts
Condition: When - Check the condition of OS family and install the package using appropriate module
Update Packages - Write a playbook to update the packages and install package

Concepts & Practicals
Introduction on Ansible Roles
Role directory structure
storing and finding roles
Using roles
Running a role multiple times in one playbook
Include and Dependency Management
Passing different parameters
Introduction on ansible tower
Tower installation and Tower Dashboard
Job oriented: Hands-On preparation
How to include a role
how to use conditionally include a role
passing other keywords, including variables and tags, when including roles
Passing different parameters in each role
How to create new roles, share roles on Galaxy, role management

Concepts & Practicals
What is Terraform?
What is IAC and how Terraform fits into it?
Why do you need Terraform?
Comparison [Terraform with other orchestration tools]
How Terraform works?
Architecture of Terraform

Job oriented: Hands-On preparation
Create an end-to-end flow-chart fitting Terraform in DevOps echo system.

Concepts & Practicals
Setup AWS Account with Free-tier option
Creating EC2 Instance & Connecting from Windows
Installing Terraform on Linux
Installing Terraform on Windows

Job oriented: Hands-On preparation
Installing production grade Terraform in your Practice Windows or Linux
Create a special IAM user account in AWS for Terraform.

Concepts & Practicals
What is Terraform HCL?
Defining Arguments & blocks in Terraform
Simple variable types - String, Integer & Boolean
Complex variable types - List, Tuple, Map & Object

Job oriented: Hands-On preparation
Create simple Terraform configuration file [with .tf extension]
Define variables such as string, integer, list & map in created config file
Call the defined variables from Terraform console
Also practice calling the Map variables by referring its Key

Concepts & Practicals
Provider block with AWS account details
Resource block with resource type details
Terraform work-flow - Create, Init, Plan & Apply
Understand the difference between plan & apply

Job oriented: Hands-On preparation
Create configuration files with Provider & Resource blocks.
Do initiate the configuration file
Trigger plan & apply

Concepts & Practicals
How to use variables in configuration file
Use variables from changing elements
Pass variables from command line
Pass variables from a file

Job oriented: Hands-On preparation
Convert all your credentials, regions or whichever possible as variables
Install EC2 instance in 2 regions with single configuration file
Provide “variable = region” at run time as a command line argument

Concepts & Practicals
How to store credentials in tfvars file
How to store credentials as an environment variable using AWS CLI.
How to pass credentials from command line.

Job oriented: Hands-On preparation
Install AWS CLI and store your credentials as an environment variable.
Provide credentials as a command line argument at run time.

Concepts & Practicals
Output the resource attributes after Terraform apply.
State file
Understand the difference between local and remote states.
Create AWS S3 bucket with versioning enabled.
How to push all your state files in S3 bucket?
Provisioner
Local provisioning
Remote provisioning
Data source
Fetch details such as [AMI ID, Availability Zone, EBS volume ID..] over API.

Job oriented: Hands-On preparation
Extract public IP to a file using Output plugin.
Push all the state files to created S3 bucket, ensure versioning is enabled
Install packages such as httpd & ntpd using provisioner plugin.
Create volume in Mumbai region at availability zone (a).
Should not hardcode the region information in code instead fetch the availability zone details over API using Data source plugin.

Create 3 IAM users using count & for_each and add those users into the existing group.
Create an EC2 instance with sequential tag names and attach it with a different VPC.
Create an EC2 instance with different tag names and attach it with different SG.
Create separate modules for EC2, EBS, VPC & EIP
Call the modules to create your production & Dev environments.
Prod environment creation with RHEL image and attach it with dedicated prod VPC.
Dev environment creation with Ubuntu image and attach it with dedicated dev VPC.
Create a separate workspace for the Prod & Dev environment to keep state files separate.

Concepts & Practicals
What is Continuous Monitoring
What is Nagios? Features & Capabilities
Necessity of Monitoring in DevOps, Use-Cases
Nagios architecture

Job oriented: Hands-On preparation
Installing Nagios on Linux - Preview
Configuring Nagios server components

Concepts & Practicals
Nagios Plugins(NRPE) and Objects
Different Monitoring Services in Nagios
What are NRPE plugins
Nagios Commands and Notification

Job oriented: Hands-On preparation
Monitoring System Info using NRPE plugins
Monitoring of different servers using Nagios

Concepts
What is DevSecOps?
Importance of Security in DevOps life-cycle
DevSecOps goals and use-cases
Left-shift approach w.r.t application security

Job oriented preparation
Importance of ‘Sec’ for delivering Secure Applications
Integrating Security tools in different phases of DevOps ecosystem

Concepts
Integrating Security tools in IDEs in development phase
Integrating Security tools in build phase
Continous secure deployments with Jenkins
Risks of using open source & License compliance check
Secirty quality gates for application deployments

Job oriented preparation
Implementation best practices, Ideating Security Integration with DevOps tools
Application Development, Build and Deployment best practices enabling Sec in DevOps
Who needs DevSecOps? Too much is process overhead. Pros & Cons.

Concepts & Practicals
Developer Security tools overview: PMD, Checkstyle, SonarQube, FindBugs ..etc.
OWASP Top Ten Web Application Security Risks
Minimizing security and license compliance risks using ‘Black Duck’ tool

Job oriented: Hands-On preparation
Understanding OWASP Top Ten Risks and implementing as part of DevOps

What is Scripting
Why Shell Scripting
What is Shell, Shell types
What is Shell interpreter
She-bang & Script execution
Executing shell scripts
Debugging
Shell script permissions
Prerequisites - Linux Commands
Job oriented: Hands-On preparation
It’s just a quick introduction. Nothing as of now

Concepts & Practicals
Defining a variable and accessing values
Variable names
Special variables
Read-only variables
Unsetting a variable
Command-line arguments
Special parameters
Exit status

Job oriented: Hands-On preparation
Understanding shell script basics
Writing basic shell scripts

Concepts & Practicals
Arithmetic Operators
Relational Operators
Boolean Operators
String Operators
File Test Operators

Job oriented: Hands-On preparation
Building the logic. Perform mathematical operations
Writing shell scripts

Concepts & Practicals
The if...else statements
The case...esac Statement
The while loop
The for loop
The until loop
The break & continue statements

Job oriented: Hands-On preparation
Writing complex scripts using language constructs
Decision making choosing right constructs for real-time use cases

Concepts & Practicals
Creating functions
Passing parameters
Returning values
Function call from prompt
Defining Array values
Accessing Array values

Job oriented: Hands-On preparation
Writing scripts using functions
Making the code reusable

Concepts & Practicals
Shell Command substitution $(CMD)
Escape Sequences
Input & Output redirection
Here Document
Job oriented: Hands-On preparation
Writing scripts using CMD substitution & file handling scenarios
Handing I/O redirection

GET AHEAD WITH DEEPNEURON DEVOPS CERTIFICATE

Earn your Aws DevOps certificate

Our Aws DevOps program is exhaustive and this certificate is proof that you have taken a big leap in mastering the domain.

Differentiate yourself with a Aws DevOps Certificate

The knowledge and Aws DevOps skills you've gained working on projects, simulations, case studies will set you ahead of the competition.

Share your achievement

Talk about it on Linkedin, Twitter, Facebook, boost your resume, or frame it - tell your friends and colleagues about it.

Aws DevOps Certificate

DeepNeuron Testimonials

-Anand Shyam,Data Scientist

"Am proud to be one of your students.I learnt Big data, Data Science and thoroughly enough.Here every session was great and very valuable. It was extremely useful and we... learnt data science concept more than what I expected."

-Y.Naidu,Project Manager

"The hands-on training sessions were very good.Your excellent explanation on statistics super....Great job with your ppts!.You have covered most of the algorithms which were never covered even by reputed institutions."

-Bhuvanesh,Senior Data Scientist

"The Training Which I Underwent From Sathya Who Is In This Industry For Long Is The Best....He Teaches Things Practically And How To Apply The Techniques Which Is Most Important , Its Worth Everything."

-Boobathy,Project Manager

"Done An Awesome Job. Am thoroughly Satisfied With The Training Provided By Sasken(A) Sathya....End of the day I felt like "I am data scientist".I recommend whoever would like to be a Big Data Analytics/ Data Scientist."

-Shiva Project Manager, CTS

I have never seen such an excellent faculty like Mr.sasken who is the best faculty . I feel very lucky and blessed to be a student ...of sasken , I would recommend anybody who has a passion..

-ThulasiDass,CSC ,Chennai

"without doubt that his (Sasken (a) Sathya) training is the best compared to others. The way he explains statistical concepts in the intuitive way is very good, so that a person without any statistics background can understand and remember the terminology very easily....The training covered all of my expectations and helping me in the process of changing my carrier from legacy based technical skill sets to emerging hot technical sill sets The content of the material, code’s(R, Python& SAS) and datasets he uses to explain various machine learning algorithms are the best compared other training institutes/trainers.

-Babu Lakshman -Cognizant

"The course is a combination of various data science concepts such as machine learning, visualization, data mining, programming, data munging. It gives hands on experience with statistical modelling techniques. The course has real world examples of how...analytics have been used to significantly improve business performance. Apart from machine learning the course introduces to map reduce, spark and Hadoop ecosystems, bias vs variance, learning curves, etc. The course gives a good understanding of R and also good introduction to Python and SAS."

-Vijay , HCL

"The training was very perfect, as the teaching approach was very clear and the pace is slow, The way the faculty explain each and every topics in detail with simples examples helped me to understand ...even the complex algorithms. The training material is really good and helpful."

FAQs

What is the objective of our Aws DevOps course training?

The objective of the Aws DevOps certification course is to provide extensive coverage on the design and deployment of Aws DevOps architecture for applications with special references to Aws DevOps tools. With DeepNeuron online course, we ensure hands-on practical experience on continuous integration and deployment for online training for Aws DevOps which will help you to master any level of Aws DevOps certification with confidence.
Why and who should go for the Aws DevOps course?

Aws DevOps is one of the top-notch technologies in cloud computing. In this modern competitive market, every small and big organization is moving into this cloud business for application and software development. Absolute beginners and experienced individuals who want to explore the Aws DevOps culture can opt for Aws DevOps training and certification. Even software developers who want to switch their careers as Aws DevOps engineers, Aws DevOps architect can gear up for certified Aws DevOps online training from DeepNeuron.
Who is my trainer and what is his selection process?

Our subject matter experts (SMEs) are experienced with industry expertise in their preferred domain and technologies. Our selection process is intriguing in reference to the course modules where we seek professional experts who have ideas and worked in the same technology for creating and deployment of applications in real-time. Professional experts SMEs will guide you through the entire module and will also make you get exposed to practice-based learning.
What can I expect after the Aws DevOps course accomplishment?

After the completion of the Aws DevOps training course, you will gain expert knowledge to master the Aws DevOps and will be a proficient player to tap Aws DevOps tools at a depth level. Moreover, you will be part of the DeepNeuron community to leverage the knowledge-base shared by the members around the globe. You will also earn an industry-recognized Aws DevOps certification from DeepNeuron.
What are the different modes of Aws DevOps training that DeepNeuron provides?

DeepNeuron offers Instructor-led online training delivered by highly experienced Aws DevOps experts holding more than 10+ years of industry experience. Our separate cherry-picked pool of subject matter experts work with respective courses in curating the best contents and study materials for greater learning experience. Take our FREE Demo sessions to witness our trainer’s expertise.
What kind of projects are included as part of this Aws DevOps training?
As a part of this Data Science online course, in collaboration with IBM, you will receive the following:
- Lifetime access to e-learning course syllabus for all of the Data Science courses included in the learning path (*only for Data2bussinessinsights courses)
- Industry-recognized certificates from IBM*(for IBM courses) and Simplilearn upon successful completion of the program
- USD 1200 worth of IBM cloud credits that you can leverage for hands-on exposure
- Access to IBM cloud platforms featuring IBM Watson and other software for 24/7 practice
*For which all courses will I get certificates from IBM?
Following are the list of courses for which you will get IBM certificates:
- R Programming for Data Science
- Python for Data Science

How do I enroll for the Data Scientist course?
You can enroll in this Data Science training on our website and make an online payment using any of the following options:
- Visa Credit or Debit Card
- MasterCard
- American Express
- Diner’s Club
- PayPal
Once payment is received you will automatically receive a payment receipt and access information via email.
If I need to cancel my enrollment, can I get a refund?

Yes, you can cancel your enrollment if necessary. We will refund the course price after deducting an administration fee. To learn more, please read our Refund Policy.
I am not able to access the online Data Science courses. Who can help me?

Yes, we do offer a money-back guarantee for many of our training programs. Refer to our Refund Policy and submit refund requests via our Help and Support. portal.
Who are the instructors and how are they selected?

All of our highly qualified Data Science trainers are industry experts with years of relevant industry experience. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating remain on our faculty.
What is Global Teaching Assistance?

Our teaching assistants are a dedicated team of subject matter experts here to help you get certified in your first attempt. They engage students proactively to ensure the course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance. Teaching Assistance is available during business hours.
What is covered under the 24/7 Support promise?

We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your course with us.
Does Deep Neuron provide practice exams related to this Data Scientist course?
Yes, we offer the following Data Science associated practice tests –
- SAS Certification Exam Practice Test
- Data Science Foundations with R Practice Test
- Data Science with Python Practice Test
- Business Analytics with Excel Practice Test
- Tableau Certification Exam Practice Test
- Power BI Exam Questions Practice Test

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Course	Course completion certificate	Criteria
Data Science and Statistics Fundamentals	Required	85% of Online Self-paced completion
Data Science with R	Required	85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and score above 75% in the course-end assessment, and successful evaluation in at least 1 project
Data Science with SAS	Required	85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and score above 75% in the course-end assessment, and successful evaluation in at least 1 project
Data Science with Python	Required	85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and score above 75% in course-end assessment and successful evaluation in at least 1 project
Machine Learning and Tableau	Required	85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and successful evaluation in at least 1 project
Big Data Hadoop and Spark Developer	Required	85% of Online Self-paced completion or attendance of 1 Live Virtual Classroom, and score above 75% in the course-end assessment, and successful evaluation of at least 1 project
Capstone Project	Required	Attendance of 1 Live Virtual Classroom and successful completion of the capstone project