Application Deadline

31st January

Batch Starts

7th Feb, 2023

8 months

Duration

Online

Format

18+

Projects

E&ICT, IIT Roorkee

Certificate

About the Course

Home All Courses Executive PG Certificate Program in Data Science & AI By E&ICT Academy, IIT Roorkee

Executive PG Certificate Program in Data Science & AI By E&ICT Academy, IIT Roorkee

The Executive Program in Data Science and AI is an intensive online instructor led course. You will master Python, NumPy, Pandas, Scikit-learn, Spark, Hadoop, Regression, Classification, SVM, ANN, Tableau that will empower you to solve complex problems and make data-informed decisions. On completing the course successfully, you will receive a certificate from IIT Roorkee that can propel your career.

(4.75K) 35K+ Learners
10 Projects + 1 Capstone 60 Days Cloud Lab Access
The Data Science market is expected to grow from USD 3.42 Billion in 2018 to USD 10.31 Billion by 2023.
The Data Science market is expected to grow from USD 3.42 Billion in 2018 to USD 10.
The Data Science market is expected to grow from USD 3.42 Billion in 2018 to USD 10.
The Data Science market is expected to grow from USD 3.42 Billion in 2018 to USD 10.

About the Course

This Executive PG Certificate Program in Data Science & AI is an online course. This course covers some of the most trending and latest technologies in the market. The cutting edge content provided through this course will help you launch a career in the field of Data Science and AI.

Additionally, this course comes with our cloud lab access to gain the much needed hands-on experience to solve the real-world problems.

Upon successfully completing the course, you will get the certificate from IIT Roorkee which you can use for progressing in your career and finding better opportunities.

Program Highlights

Executive PG Certificate from IIT Roorkee

Executive PG Certificate from E&ICT Academy, IIT Roorkee

Certificate of Completion by E&ICT Academy, IIT Roorkee

Placement Eligibility Test

Placement Eligibility Test

Proctored Exams with opportunity to get Placed

Hands-On Project

18+ Hands-On Project

Work on real world projects to get an hands-on experience

Timely Doubt Resolution

Timely Doubt Resolution

Get access to community of learners via our discussion forum

Access to Cloud Lab

Access to Cloud Lab

Lab comes pre-installed with all the software you will need to learn and practice.

Application Deadline 31st Jan'23

Apply Now (14 Seats Left) Request a Callback

Our Students Work At

And More

Certificate

What is the certificate like?

Executive PG Certificate Program in Data Science By IIT Roorkee

Course Certificate

  • Why E&ICT, IIT Roorkee?

    Electronics & ICT Academy IIT Roorkee (E&ICT IITR), provides certification courses with emphasis on hands-on learning in basic/advanced topics and emerging technologies in the Electronics and ICT domain. It is sponsored by Ministry of Electronics and Information Technology, Govt. of India. We conduct certification courses/short courses/FDPs in the emerging areas to enrich & upgrade subject knowledge and technical skills benefiting students, working professionals, Govt. employees and Faculty members. The trained beneficiaries are expected to create a cascading effect, transforming the competencies and standards in the parent institutes/organizations. E&ICT courses are at par with QIP for recognition/credits. So far the E&ICT Academy, IIT Roorkee has conducted 150+ courses and trained over 10,000 beneficiaries.

  • Why CloudxLab?

    CloudxLab is a team of developers, engineers, and educators passionate about building innovative products to make learning fun, engaging, and for life. We are a highly motivated team who build fresh and lasting learning experiences for our users. Powered by our innovation processes, we provide a gamified environment where learning is fun and constructive. From creative design to intuitive apps we create a seamless learning experience for our users. We upskill engineers in deep tech - make them employable & future-ready.

Campus Immersion Program

A 3 day Campus immersion Program was organized at IIT Roorkee to supplement online learning. Leaners get a chance to have physical experiences such as 1:1 with Professors and Industry Experts, networking with peers and consulting for projects. They also get a chance to showcase and explain their projects presentation to fellow learners. Hard Copy of certificates were also awarded at the end of the function.

QS

#1st

Among the IITs in the ‘Citations per Faculty’ parameter

*QS World Rankings

India Today

#5

Ranked Engineering College

*India Today 2020

NIRF

#6

Ranked for IITs

*NIRF 2020

QS

#12

Ranked Best Global Universities in India

*QS World Rankings

Programming Languages and Tools

Hands-on Learning

hands-on lab

  • Gamified Learning Platform
    Making learning fun and sustainable

  • Auto-assessment Tests
    Learn by writing code and executing it on lab

  • No Installation Required
    Lab comes pre-installed softwares and accessible everywhere


Mentors / Faculty

Instructor Tharun Reddy

Tharun Kumar Reddy Bollu

Faculty ECE Dept

IIT Roorkee

Instructor Raksha Sharma

Raksha Sharma

Faculty CSE Dept

IIT Roorkee

Instructor Sanjeev Manhas

Sanjeev Manhas

Faculty ECE Dept

IIT Roorkee

Dr. M.L. Virdi

Dr. M.L. Virdi

Senior Research Scientist

NASA

Instructor Sandeep Giri

Sandeep Giri

Founder at CloudxLab

Past: Amazon, InMobi, D.E.Shaw

Instructor Abhinav Singh

Abhinav Singh

Co-Founder at CloudxLab

Past: Byjus

Instructor Praveen

Praveen Pavithran

Co-Founder at Yatis

Past: YourCabs, Cypress Semiconductor

Curriculum

Foundation Courses

1. Programming Tools and Foundational Concepts
1. Linux for Data Science
2. Getting Started with Git
3. Python Foundations
4. Machine Learning Prerequisites(Including Numpy, Pandas and Linear Algebra)
5. Getting Started with SQL
6. Statistics Foundations

Course on Machine Learning

1. Machine Learning Applications & Landscape
1. Introduction to Machine Learning
2. Machine Learning Application
3. Introduction to AI
4. Different types of Machine Learning - Supervised, Unsupervised
2. Building end-to-end Machine Learning Project
1. Machine Learning Projects Checklist
2. Get the data
3. Launch, monitor, and maintain the system
4. Explore the data to gain insights
5. Prepare the data for Machine Learning algorithms
6. Explore many different models and short-list the best ones
7. Fine-tune model
3. Training Models
1. Linear Regression
2. Gradient Descent
3. Polynomial Regression
4. Learning Curves
5. Regularized Linear Models
6. Logistic Regression
4. Support Vector Machines
1. Linear SVM Classification
2. Nonlinear SVM Classification
3. SVM Regression
5. Decision Trees
1. Training and Visualizing a Decision Tree
2. Making Predictions
3. Estimating Class Probabilities
4. The CART Training Algorithm
5. Gini Impurity or Entropy
6. Regularization Hyperparameters
7. Instability
6. Ensemble Learning and Random Forests
1. Voting Classifiers
2. Bagging and Pasting
3. Random Patches and Random Subspaces
4. Random Forests
5. Boosting and Stacking
7. Dimensionality Reduction
1. The Curse of Dimensionality
2. Main Approaches for Dimensionality Reduction
3. PCA
4. Kernel PCA
5. LLE
6. Other Dimensionality Reduction Techniques

Course on Deep Learning

1. Introduction to Artificial Neural Networks
1. From Biological to Artificial Neurons
2. Implementing MLPs using Keras with TensorFlow Backend
3. Fine-Tuning Neural Network Hyperparameters
2. Convolutional Neural Networks
1. The Architecture of the Visual Cortex
2. Convolutional Layer
3. Pooling Layer
4. CNN Architectures
5. Classification with Keras
6. Transfer Learning with Keras
7. Object Detection
8. YOLO
3. Natural Language Processing
1. Introduction to Natural Language Processing
2. Creating a Quiz Using TextBlob
3. Finding Related Posts with scikit-learn
4. Generating Shakespearean Text Using Character RNN
5. Sentiment Analysis
6. Encoder-Decoder Network for Neural Machine Translation
7. Attention Mechanisms
8. Recent Innovations in Language Models
4. Reinforcement Learning
1. Learning to Optimize Rewards
2. Policy Search
3. Introduction to OpenAI Gym
4. Neural Network Policies
5. Evaluating Actions: The Credit Assignment Problem
6. Policy Gradients
7. Markov Decision Processes
8. Temporal Difference Learning and Q-Learning
9. Deep Q-Learning Variants
10. The TF-Agents Library

Complimentary Topics

1. Introduction to Hadoop
1. Introduction
2. Distributed systems
3. Big Data Use Cases
4. Various Solutions
5. Overview of Hadoop Ecosystem
6. Spark Ecosystem Walkthrough
2. Foundation & Environment
1. Understanding the CloudxLab
2. Getting Started - Hands on
3. Hadoop & Spark Hands-on
4. Understanding Regular Expressions
5. Setting up VM
3. Zookeeper
1. ZooKeeper - Race Condition
2. ZooKeeper - Deadlock
3. How does election happen - Paxos Algorithm?
4. Use cases
5. When not to use
4. HDFS
1. Why HDFS?
2. NameNode & DataNodes
3. Advance HDFS Concepts (HA, Federation)
4. Hands-on with HDFS (Upload, Download, SetRep)
5. Data Locality (Rack Awareness)
5. YARN
1. Why YARN?
2. Evolution from MapReduce 1.0
3. Resource Management: YARN Architecture
4. Advance Concepts - Speculative Execution
6. MapReduce Basics
1. Understanding Sorting
2. MapReduce - Overview
3. Word Frequency Problem - Without MR
4. Only Mapper - Image Resizing
5. Temperature Problem
6. Multiple Reducer
7. Java MapReduce
7. MapReduce Advanced
1. Writing MapReduce Code Using Java
2. Apache Ant
3. Concept - Associative & Commutative
4. Combiner
5. Hadoop Streaming
6. Adv. Problem Solving - Anagrams
7. Adv. Problem Solving - Same DNA
8. Adv. Problem Solving - Similar DNA
9. Joins - Voting
10. Limitations of MapReduce
8. Analyzing Data with Pig
1. Pig - Introduction
2. Pig - Modes
3. Example - NYSE Stock Exchange
4. Concept - Lazy Evaluation
9. Processing Data with Hive
1. Hive - Introduction
2. Hive - Data Types
3. Loading Data in Hive (Tables)
4. Movielens Data Processing
5. Connecting Tableau and HiveServer 2
6. Connecting Microsoft Excel and HiveServer 2
7. Project: Sentiment Analyses of Twitter Data
8. Advanced - Partition Tables
9. Understanding HCatalog & Impal
10. NoSQL and HBase
1. NoSQL - Scaling Out / Up
2. ACID Properties and RDBMS Story
3. CAP Theorem
4. HBase Architecture - Region Servers etc
5. Hbase Data Model - Column Family Orientedness
6. Getting Started - Create table, Adding Data
7. Adv Example - Google Links Storage
8. Concept - Bloom Filter
9. Comparison of NOSQL Databases
11. Importing Data with Sqoop and Flume, Oozie
1. Sqoop - Introduction
2. Sqoop Import - MySQL to HDFS
3. Exporting to MySQL from HDFS
4. Concept - Unbounding Dataset Processing or Stream Processing
5. Flume Overview: Agents - Source, Sink, Channel
6. Data from Local network service into HDFS
7. Example - Extracting Twitter Data
8. Example - Creating workflow with Oozier
12. Introduction to Spark
1. Apache Spark ecosystem walkthrough
2. Spark Introduction - Why Spark?
13. Scala Basics
1. Introduction, Access Scala on CloudxLab
2. Variables and Methods
3. Interactive, Compilation, SBT
4. Types, Variables & Values
5. Functions
6. Collections
7. Classes
8. Parameters
14. Spark Basics
1. Apache Spark ecosystem
2. Why Spark?
3. Using the Spark Shell on CloudxLab
4. Example 1 - Performing Word Count
5. Understanding Spark Cluster Modes on YARN
6. RDDs (Resilient Distributed Datasets)
7. General RDD Operations: Transformations & Actions
8. RDD lineage
9. RDD Persistence Overview
10. Distributed Persistence
15. Writing and Deploying Spark Applications
1. Creating the SparkContext
2. Building a Spark Application (Scala, Java, Python)
3. The Spark Application Web UI
4. Configuring Spark Properties
5. Running Spark on Cluster
6. RDD Partitions
7. Executing Parallel Operations
8. Stages and Tasks
16. Common Patterns in Spark Data Processing
1. Common Spark Use Cases
1. Example 1 - Data Cleaning (Movielens)
1. Example 2 - Understanding Spark Streaming
2. Understanding Kafka
3. Example 3 - Spark Streaming from Kafka
4. Iterative Algorithms in Spark
5. Project: Real-time analytics of orders in an e-commerce company
17. Data Formats & Management
1. XML
2. AVRO
3. How to store many small files - SequenceFile?
4. Parquet
5. Protocol Buffers
6. Comparing Compressions
7. Understanding Row Oriented and Column Oriented Formats - RCFile?
18. DataFrames and Spark SQL
1. Spark SQL - Introduction
2. Spark SQL - Dataframe Introduction
3. Transforming and Querying DataFrames
4. Saving DataFrames
5. DataFrames and RDDs
6. Comparing Spark SQL, Impala, and Hive-on-Spark
19. Machine Learning with Spark
1. Machine Learning Introduction
2. Applications Of Machine Learning
3. MlLib Example: k-means
4. SparkR Example
20. Classification
1. Training a Binary classification
2. Multiclass,Multilabel and Multioutput Classification
3. Performance Measures
4. Confusion Matrix
5. Precision and Recall
6. Precision/Recall Tradeoff
7. The ROC Curve
21. Training Deep Neural Networks
1. The Vanishing / Exploding Gradients Problems
2. Reusing Pretrained Layers
3. Faster Optimizers
4. Avoiding Overfitting Through Regularization
5. Practical Guidelines to Train Deep Neural Networks
22. Custom Models and Training with Tensorflow
1. A Quick Tour of TensorFlow
2. Customizing Models and Training Algorithms
3. Tensorflow Functions and Graphs
23. Loading and Preprocessing Data with TensorFlow
1. Introduction to the Data API
2. TFRecord Format
3. Preprocessing the Input Features
4. TF Transform
5. The TensorFlow Datasets (TDFS) Projects
24. Recurrent Neural Networks
1. Recurrent Neurons and Layers
2. Basic RNNs in TensorFlow
3. Training RNNs
4. Deep RNNs
5. Forecasting a Time Series
6. LSTM Cell
7. GRU Cell
25. Autoencoders and GANs
1. Efficient Data Representations
2. Performing PCA with an Under Complete Linear Autoencoder
3. Stacked Autoencoders
4. Unsupervised Pre Training Using Stacked Autoencoders
5. Denoising Autoencoders
6. Sparse Autoencoders
7. Variational Autoencoders
8. Generative Adversarial Networks
8+
Months of Blended Training
240
Days of Lab Access
18+
Projects
13K+
Learners
Download Curriculum

Projects

Apply Now

Application Process


  • Step 1. Submit the application form and SOP(Statement of Purpose)
    Register by filling the application form. Admission Test in the next step will be immediately after filling the form.

  • Step 2. Admission Test
    Online admission test of 20 minutes containing 15 multiple choice questions to assess your quantitative aptitude and programming skills.

  • Step 3. Personal Interview
    Online personal interview with a course mentor. The interviewer will ask questions based on your Statement of Purpose, work experience(if any) and your motivation and aspirations to join the course.

  • Step 4. Join The Program
    If selected, the admission office will send the letter of acceptance. Submit the admission fees in due time to confirm the seat

    • Note: Admission test should be taken immediately after submitting the application using the link displayed post application submission.


Eligibility Criteria

    1. Anybody in their final year of undergraduate degree or has completed their undergraduation is eligible to apply for the course
    1. Must have studied Mathematics in 12th standard

Scholarships

    1. 10% Scholarships are available for students, women from STEM background and unemployed
    1. 5% Scholarship available for IIT Alumni and CloudxLab Alumni.
    1. Bring your friend along and avail discount upto 10%.

PS: Details to avail the scholarship will be sent post application-submission and only one scholarship applicable per learner

Certification Guideline

Learners are expected to complete at least 80% of the course content and any 3 of the mandatory projects within 180 days of batch commencement to be eligible for the certificate.

Program Fee

2,999* 5,998

Or pay in EMI starting at 249*/Month

  • 8 Months Program
  • 240 Days of Online Lab Access
  • 24*7 Support
  • Batch Starts on 7th Feb'23
  • Certificate from E&ICT Academy, IIT Roorkee
Apply Now»

  • Note: Apply for scholarship and avail discount upto 10%

    • Placement Assistance

    By CloudxLab

    Placement Eligibility Test

    Placement Eligibility Test

    We have around 300+ recruitment partners who will be interviewing you based on your performances in PET

    Dedicated Job Portal

    Dedicated Job Portal

    Opportunities from companies who approach us asking for our learner profiles will be posted on our job portal to providevisibility to your profile

    Career Guidance Webinars

    Career Guidance Webinars

    Career Guidance Webinars from seasoned industry experts

    Testimonials

    ​