Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Course Overview
The Executive PG Certificate Program in Data Science By IIT Roorkee course is a 12 months online course that is created by IIT Roorkee, on the platform of CloudxLab. This certification course holds an immersion programme for all the participants before the course starts that helps gain a first-hand understanding of the programme. This certificate course also offers lucrative scholarships and options of no-cost EMI that make it smooth for the student to pay their fee.
The Executive PG Certificate Program in Data Science By IIT Roorkee training course covers trending and latest technological concepts in the market. This course will help students launch their careers in the Data Science field. Also, this course provides unlimited access to the content on the cloud lab so that the candidates gain experience by solving practical problems. The certification course also arranges for participants to attend proctored eligibility tests to get placed comfortably.
The Highlights
- 12 months course duration
- Online classes conducted
- Hands-on course curriculum
- Certificate from IIT Roorkee
- 1-week immersion programme
Programme Offerings
- 12 months course
- Online Sessions
- Blended training
- Cloud lab access
- Projects
- 13 K+ Learners
- Renounced Mentors
- Auto-Assessment Tests
- Hands-on Learning
- programming languages
- Programming Tools
- timely doubt resolution
- completion certificate
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | IIT Roorkee |
The Executive PG Certificate Program in Data Science By IIT Roorkee fee is Rs. 2,49,999, where if the students use the no-cost EMI option facility, then the students can pay as low as Rs. 19,091 per month. Sometimes when the students get ready to pay the total fee at one time then they can get a 5% discount.
Executive PG Certificate Program in Data Science By IIT Roorkee Fee Structure
Description | Fee in INR |
Programme Fee | Rs. 2,49,999 |
Eligibility Criteria
Educational Qualification
Students should either be in their undergraduate degree final year or must have already completed their undergraduate. Also, these students must have learnt mathematics in the class 12 syllabi.
Certification Qualifying Details
To obtain the Executive PG Certificate Program in Data Science By IIT Roorkee, the students must finish 75% of the course, 6 guided projects, and 1 capstone project within the 12 months of the course.
What you will learn
The Executive PG Certificate Program in Data Science By IIT Roorkee syllabus will give extensive knowledge in topics of business analytics, machine learning, programming tools, data science, Big Data with Hadoop and Spark, and more.
Who it is for
Students who are interested in data science learning and have maths as a plus 2 subject, and are a graduate or in their final year of graduation are welcome to pursue this to become a data scientist.
Admission Details
Here is the Executive PG Certificate Program in Data Science By IIT Roorkee classes admission process:
Step 2: The candidates next have to register by filling, and submitting the application form and statement of purpose.
Step 3: Next, the students need to attend a 60 minutes admission test with all 20 multiple-choice questions.
Step 4: Then, the students will also go through an interview online with a course mentor for 45 minutes.
Step 5: After selection, the letter of acceptance will be sent by the admission office.
Step 6: Finally, the admission is confirmed only when the participants in due time submit the fees.
Application Details
Some important details for the application are name, email address, mobile number, date of birth, GitHub profile, Linkedin profile handles, and more. These details all fall under the mandatory category which when filled up for around 20 minutes, only then students will be allowed for admission test participation.
The Syllabus
Programming Tools & Foundational Concepts
- Linux for Data Science
- Getting Started with Git
- Python Foundations
- Machine Learning Prerequisites(Including Numpy, Pandas, and Linear Algebra)
- Getting Started with SQL
- Statistics Foundations
Machine Learning Applications & Landscape
- Introduction to Machine Learning
- Machine Learning Application
- Introduction to AI
- Different types of Machine Learning - Supervised, Unsupervised
Building end-to-end Machine Learning Project
- Machine Learning Projects Checklist
- Get the data
- Launch, monitor, and maintain the system
- Explore the data to gain insights
- Prepare the data for Machine Learning algorithms
- Explore many different models and short-list the best ones
- Fine-tune model
Classification
- Training a Binary classification
- Multiclass, Multilabel and Multi-output Classification
- Performance Measures
- Confusion Matrix
- Precision and Recall
- Precision/Recall Tradeoff
- The ROC Curve
Training Models
- Linear Regression
- Gradient Descent
- Polynomial Regression
- Learning Curves
- Regularized Linear Models
- Logistic Regression
Support Vector Machines
- Linear SVM Classification
- Nonlinear SVM Classification
- SVM Regression
Decision Trees
- Training and Visualizing a Decision Tree
- Making Predictions
- Estimating Class Probabilities
- The CART Training Algorithm
- Gini Impurity or Entropy
- Regularization Hyperparameters
- Instability
Ensemble Learning and Random Forests
- Voting Classifiers
- Bagging and Pasting
- Random Patches and Random Subspaces
- Random Forests
- Boosting and Stacking
Dimensionality Reduction
- The Curse of Dimensionality
- Main Approaches for Dimensionality Reduction
- PCA
- Kernel PCA
- LLE
- Other Dimensionality Reduction Techniques
Analytics Tools
- PowerBI
- Tableau
- Market Basket Analysis
- RFM segmentation
Introduction to Hadoop
- Introduction
- Distributed systems
- Big Data Use Cases
- Various Solutions
- Overview of Hadoop Ecosystem
- Spark Ecosystem Walkthrough
Foundation & Environment
- Understanding the CloudxLab
- Getting Started - Hands-on
- Hadoop & Spark Hands-on
- Understanding Regular Expressions
- Setting up VM
Zookeeper
- ZooKeeper - Race Condition
- ZooKeeper - Deadlock
- How does an election happen - Paxos Algorithm?
- Use cases
- When not to use
HDFS
- Why HDFS?
- NameNode & DataNodes
- Advance HDFS Concepts (HA, Federation)
- Hands-on with HDFS (Upload, Download, SetRep)
- Data Locality (Rack Awareness)
YARN
- Why YARN?
- Evolution from MapReduce 1.0
- Resource Management: YARN Architecture
- Advance Concepts - Speculative Execution
MapReduce Basics
- Understanding Sorting
- MapReduce - Overview
- Word Frequency Problem - Without MR
- Only Mapper - Image Resizing
- Temperature Problem
- Multiple Reducer
- Java MapReduce
MapReduce Advanced
- Writing MapReduce Code Using Java
- Apache Ant
- Concept - Associative & Commutative
- Combiner
- Hadoop Streaming
- Adv. Problem Solving - Anagrams
- Adv. Problem Solving - Same DNA
- Adv. Problem Solving - Similar DNA
- Joins - Voting
- Limitations of MapReduce
Analyzing Data with Pig
- Pig - Introduction
- Pig - Modes
- Example - NYSE Stock Exchange
- Concept - Lazy Evaluation
Processing Data with Hive
- Hive - Introduction
- Hive - Data Types
- Loading Data in Hive (Tables)
- Movielens Data Processing
- Connecting Tableau and HiveServer 2
- Connecting Microsoft Excel and HiveServer 2
- Project: Sentiment Analyses of Twitter Data
- Advanced - Partition Tables
- Understanding HCatalog & Impa
NoSQL and HBase
- NoSQL - Scaling Out / Up
- ACID Properties and RDBMS Story
- CAP Theorem
- HBase Architecture - Region Servers etc
- Hbase Data Model - Column Family Orientedness
- Getting Started - Create table, Adding Data
- Adv Example - Google Links Storage
- Concept - Bloom Filter
- Comparison of NOSQL Databases
Importing Data with Sqoop and Flume, Oozie
- Sqoop - Introduction
- Sqoop Import - MySQL to HDFS
- Exporting to MySQL from HDFS
- Concept - Unbounding Dataset Processing or Stream Processing
- Flume Overview: Agents - Source, Sink, Channel
- Data from Local network service into HDFS
- Example - Extracting Twitter Data
- Example - Creating a workflow with Oozier
Introduction to Spark
- Apache Spark ecosystem walkthrough
- Spark Introduction - Why Spark?
Scala Basics
- Introduction, Access Scala on CloudxLab
- Variables and Methods
- Interactive, Compilation, SBT
- Types, Variables & Values
- Functions
- Collections
- Classes
- Parameters
Spark Basics
- Apache Spark ecosystem
- Why Spark?
- Using the Spark Shell on CloudxLab
- Example 1 - Performing Word Count
- Understanding Spark Cluster Modes on YARN
- General RDD Operations: Transformations & Actions
- RDD lineage
- RDD Persistence Overview
- Distributed Persistence
Writing and Deploying Spark Applications
- Creating the SparkContext
- Building a Spark Application (Scala, Java, Python)
- The Spark Application Web UI
- Configuring Spark Properties
- Running Spark on Cluster
- RDD Partitions
- Executing Parallel Operations
- Stages and Tasks
Common Patterns in Spark Data Processing
- Common Spark Use Cases
- Example 1 - Data Cleaning (Movielens)
- Example 2 - Understanding Spark Streaming
- Understanding Kafka
- Example 3 - Spark Streaming from Kafka
- Iterative Algorithms in Spark
- Project: Real-time analytics of orders in an e-commerce company
Data Formats & Management
- XML
- AVRO
- How to store many small files - SequenceFile?
- Parquet
- Protocol Buffers
- Comparing Compressions
- Understanding Row Oriented and Column Oriented Formats - RCFile?
DataFrames and Spark SQL
- Spark SQL - Introduction
- Spark SQL - Dataframe Introduction
- Transforming and Querying DataFrames
- Saving DataFrames
- DataFrames and RDDs
- Comparing Spark SQL, Impala, and Hive-on-Spark
Machine Learning with Spark
- Machine Learning Introduction
- Applications Of Machine Learning
- MlLib Example: k-means
- SparkR Example
Instructors
IIT Roorkee Frequently Asked Questions (FAQ's)
The discount shared is 5% on one-time fee payment.
Access is given for 365 days.
There are 18+ projects held related to this IIT Roorkee.
The immersion programme’s duration is 1 week.
The admission test has to be taken online immediately after the application is submitted.