11 months

Duration

Online

Format

29+

Projects

E&ICT, IIT Roorkee

Certificate

180

Ratings

13,500+

Learners

E&ICT

E&ICT Academy, IIT Roorkee

An initiative of Ministry of Electronics and Information Technology (MeitY) Govt. of India

About the Course

This Data Science and AI Certification Program is an online course. This course covers some of the most trending and latest technologies in the market like Tensorflow 2.0, Generative Adversarial Networks (GANs) etc. The cutting edge content provided through this course will help you launch a career in the field of Data Science

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 E&ICT Academy, IIT Roorkee which you can use for progressing in your career and finding better opportunities.

Program Highlights

  • Certificate of Completion by E&ICT Academy, IIT Roorkee

  • 11 Months of Blended Learning

  • Work on about 29+ projects to get hands-on experience

  • Timely Doubt Resolution

  • Best In Class Curriculum

  • Cloud Lab Access

Certificate

What is the certificate like?

  • 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 (CxL) has been a pioneer in the edtech space for the past few years. Founded in 2015 by Sandeep Giri, an alumnus of IIT Roorkee, CxL has successfully transformed 1,000's of students' careers by offering world-class certification courses in big data, machine learning and artificial intelligence.

    Some of the unique features of CxL are an exclusive gamified learning environment through the lab (read as CloudxLab), highest rated faculty, excellent student support and more.

Hands-on Learning

hands-on lab
  • Gamified Learning Platform


  • Auto-assessment Tests


  • No Installation Required

d

Mentors / Faculty

Instructor Raksha Sharma

Raksha Sharma

Faculty CSE Dept

IIT Roorkee

Instructor Gaurav Dixit

Gaurav Dixit

Faculty DoMS Dept

IIT Roorkee

Instructor Sanjeev Manhas

Sanjeev Manhas

Faculty ECE Dept

IIT Roorkee

Mentor Venkat Karun

Venkat Karun

Staff Software Engineer

Google

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

11+
Months of Blended Training
330
Days of Lab Access
29+
Projects
13K+
Learners
Foundation
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

Machine Learning & Deep Learning

1. Introduction to Machine Learning and Deep Learning
In this topic, we will cover concepts like different types of Machine Learning algorithms (Supervised, Unsupervised, Reinforcement) and challenges in Machine Learning. We will see examples of solving the problems using the traditional approach and why Machine Learning algorithms give far better accuracy than the traditional approach. This topic will give you a brief introduction to both Machine Learning and Deep Learning world.
2. Data Preprocessing, Regression - Build end-to-end Machine Learning Project
We will start the course by learning concepts in Machine Learning. In this topic, we will build a machine learning model to predict housing pricing in California. By the end of this project, you will understand how to build machine learning pipelines to build a model. We will also cover concepts like data cleaning, preparing data for machine learning algorithms, exploring many different models, short-list the best one and fine-tuning the selected model
3. Classification
In this topic, we will train a model on the MNIST dataset to recognize handwritten digits. We will also learn various performance measures in classification like Confusion Matrix, Precision and Recall, and ROC Curve.
4. Machine Learning Algorithms
In this topic, we will learn various Machine Learning algorithms and concepts like Unsupervised Learning, Ensemble Learning, and Dimensionality Reduction
5. Introduction to Artifical Neural Networks with Keras
We will start the Deep Learning course with Artificial Neural Networks. We will learn about biological neurons, multilayer perceptrons, and back-propagation. We will implement a multilayer perceptron using Keras and visualize the runs and graphs using Tensorboard
6. Training Deep Neural Networks
In this topic, we will learn various challenges deep neural networks face while training like vanishing and exploding gradients. We will learn various techniques to solve these problems like reusing pre-trained layers, using faster optimizers and avoiding overfitting by regularization.
7. Custom Models and Training with TensorFlow
In this topic, we will dive deeper into TensorFlow and its lower level Python API. These lower-level Python APIs are useful when we need extra control like writing custom loss function, layers and many more.
81. Loading and Preprocessing Data with TensorFlow
Deep Learning systems are usually trained on very large datasets that may not fit in the RAM. In this topic, we will learn TensorFlow's Data API which helps in ingesting dataset and preprocessing it efficiently.
9. Deep Computer Vision using Convolutional Neural Network
In this topic, we will learn how Convolutional Neural Networks - CNNs achieve superhuman performance on complex visual tasks. Today CNNs power image search services, self-driving cars, automatic video classification systems and more. We will learn CNNs basic building blocks and how to implement them using TensorFlow and Keras
10. Processing Sequences Using RNNs and CNNs
Predicting the future is something we do all the time like predicting stock prices. In this topic, we will learn how Recurrent Neural Networks - RNN predict the future, the problem they face like limited short-term memory and solutions to these problems - LSTM (Long Short-Term Memory) and GRU cells
11. Natural Language Processing Concepts and RNNs
Using Natural Language Processing we build systems that can read and write natural language. In this topic, we will learn different NLP techniques and generate Shakespearean text using a Character RNN.
12. Representation Learning & Generative Learning Using autoencoders and GANs
Autoencoders are artificial neural networks capable of learning dense representations of input data without any supervision. For example, we could train an autoencoder on pictures of faces and it can then generate new faces. In this topic, we will learn different types of autoencoders and generative models.
13. Reinforcement Learning
Reinforcement Learning is one of the most exciting fields of Machine Learning. Using Reinforcement Learning AlphaGo(system) defeated the world champion at the game of Go. Reinforcement Learning is an area of Machine Learning aimed at creating agents capable of taking actions in an environment in a way that maximizes rewards over time. In this topic, we will learn various concepts in Reinforcement Learning and experiment with OpenAI Gym.

Course on Big Data with Hadoop

1. Introduction
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

Projects

Apply Now

Application Process

  • 1. Submit the application form with basic details (including motivation to join the course) followed by a quiz
  • 2. The admission team will review the application and respond with the application status in 48 hours
  • 3. Confirmation of seat is subject to the payment

Scholarship Details

  • Based on Online Scholarship Test
    1. Scholarship Test for the Batch will be conducted (Dates to be announced soon) . Format of the test will be MCQs. Test link will be circulated before one day of the test date. Top 20 Users will get 10% discount, then 5% discount for next 10 Users.
  • If you receive the Scholarship, you will need to make the payment and then the amount will be refunded.

No Cost EMI at

164/Month

Or Program Fee 1799

  • 11 Months of Blended Learning
  • 330 Days of Online Lab Access
  • 24*7 Support
  • Batch Starts on March 21, 2021
  • Certificate from E&ICT Academy, IIT Roorkee
Apply Now

Testimonials

Frequently Asked Questions

What things do i need to fulfill to claim the certificate for Data Science Specialization?

You need to complete at least 60% of the topics from the course. You also need to complete projects - Analyse emails from Python, Sentiment Analysis (Hive) from Hadoop, Log Parsing from Spark, any 3 projects from Machine Learning and any 2 projects from Deep Learning. All the above requirements need to be met within 330 days from the course enrollment date to be eligible for the certificate.

Do I need to install any software before starting this course?

No, we will provide you with the access to our online lab and BootML so that you do not have to install anything on your local machine

What options do I have if my deadline to earn the E&ICT academy, IIT Roorkee certificate is over?

Please note that you will not get a certificate from EICT academy, IIT Roorkee if your deadline to earn the EICT academy, IIT Roorkee certificate is over. You have two options in such case-

  1. Complete all the topics to 100% and earn the certificate by CloudxLab. Here is the sample certificate from CloudxLab
  2. Purchase the course again and finish the formalities to earn EICT academy, IIT Roorkee certificate within the new deadlines. Contact us for the 25% discount code for purchasing the course again.

Please note though course access is valid for the lifetime, to earn the EICT academy, IIT Roorkee certificate, you are required to finish the formalities within the stipulated deadlines. You can renew the lab anytime here

Is it an online course?

It is a self-paced course. You will get access to videos, quizzes, hands-on assessments and projects. If you have any doubts during your learning journey, you can post it on the discussion forum. Our experts and community will assist you over there.

How to view the course after getting access to it?

Please log in at CloudxLab.com with your Gmail Id and access your course under "My Courses".

What are the prerequisites and requirements for this course?

This course is for engineers, product managers and anyone who wants to learn. We will cover foundations of linear algebra, calculus and statistical inference where ever required so that you can learn the concepts effectively. There is no prerequisite or programming knowledge required.

What is the refund policy for courses taken from CloudxLab?

For self-paced course, we provide 100% fees refund if the request is raised within 7 days from enrollment date. Please contact us at reachus@cloudxlab.com to request a refund within the stipulated time. Thereafter, no refund is provided.

When will I get the certificate after submitting the projects?

Please mail your required projects at reachus@cloudxlab.com. After submitting the projects, our course experts will review it and forward your details to EICT, IIT Roorkee. EICT will be issuing your certificate, it may take 3-7 days.