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IIT Palakkad | Professional Certificate Programme In Applied Data Science

Data : The Key To Business Breakthroughs Today

Course Snapshot
  • FeeINR 75,000 + GST
  • Work Experience5+ Years
  • Duration26 Weeks
  • Delivery MethodOnline
Course Detail

Program Overview
Data is an integral part of any modern business. Collating, understanding and analysing data helps you build winning strategies which begets happier customers, stronger growth and content employees. Even in the current climate, the demand for data science professionals is at an all-time high.
The Indian Institute of Technology, Palakkad has designed the Professional Certificate Programme in Applied Data Science with a focus on upskilling the participant on Python, the world’s #1 programming language, and Data Engineering. This programme is curated for professionals interested in building a career in Data Science.

Who Is This Programme For
IIT Palakkad's programme in Applied Data Science is for professionals who want to understand the inner working of the world of Data Science to give them an advantage in the market.
This programme is ideal for early and mid-level professionals keen to upskill and gain cutting-edge knowledge in Data Science to give them an opportunity to make a career shift or to help them accelerate their careers.
Additionally, the Applied Data Science programme is aimed at executives overseeing software development who are looking to equip themselves with an up-to-date understanding in Data Science practices.

Program Highlights
● 4 Office Hours with Faculty
● 65 Recorded Video Lectures
● 12 Assignments and 12 Discussions
● Peer Learning and Feedback
● Dedicated Programme Support
● 26-week programme, 4-6 hours of weekly learning effort

Desired Candidate Profile

● Any Graduate or Diploma Holder

Course Modules

Module 1 : Statistics For Data Science
- Probability - Joint, Conditional, Marginal Probability
- DistributionsUnivariate Analysis
- Bivariate Analysis
- Multivariate Analysis
- Sample and Population
- Sampling Techniques
- Sampling Size Calculations
- Correlation, Covariance and Interquartile Ranges Inferential Analysis-Hypothesis Testing

Module 2 : Python For Data Science
- Introduction to Data Science
- Working with Data Types and Operators in Python Writing Functions in Python
- Popular Data Science Packages in Python
- Advanced Functions
- Data Manipulation and Analysis with Pandas
- Data Visualization with Matplotlib
- Random Variables and Statistical Inferences
- Statistical Distributions and Hypothesis Testing
- Data Cleaning
- Exploratory Data Analysis
- Getting Started with Linear Algebra for Machine Learning

Module 3 : Applied Data Science
- Data Engineering
- Data Storage
- Data Visualization
- Classification and Decision Trees Linear and non - linear regression Evaluating Data Models
- Time series analysis forecasting Clustering Models
- Exploratory Data Analysis
- Topic Model
- Text Analysis
- Social Network Analysis