Institute of Data Science

Data Science & AI-powered analytics

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COURSE

Introduction

This course is designed to help you gain comprehensive knowledge and hands-on experience in Data Science, Machine Learning, and Artificial Intelligence. Through practical labs, real-world projects, and essential theory, you will develop the technical expertise to solve data-driven problems across industries like finance, healthcare, and technology.

  • Apply core mathematical principles—such as linear algebra, probability, and statistics—to support data science and machine learning.
  • Efficiently prepare, preprocess, and analyze data using Python libraries like NumPy and Pandas to build high-performance models & produce insightful visualizations.
  • Implement and fine-tune supervised and unsupervised learning algorithms to address a wide range of real-world challenges.
  • Process and extract valuable insights from textual data using modern natural language processing techniques.
  • Design, build, and optimize deep neural networks with tools such as TensorFlow & Keras, while exploring advanced deep learning strategies.

What you will learn?

Master the data science lifecycle from data acquisition to model deployment.

Implement exploratory data analysis and feature engineering techniques.

Apply machine learning algorithms and understand their strengths and limitations.

Build and evaluate NLP and deep learning models.

Work with real data in a project-based environment.

Skillset you will acquire

Machine learning model development

Model evaluation and tuning

Data wrangling and analysis

Python programming for data science

NLP and neural networks

Data visualization and storytelling

Soft skills overview

Master communications, collaboration, and problem-solving skills required for modern tech roles.
Practical experience in professional environments via mock interviews and real-world scenarios.
Learn how to effectively present and collaborate in team environments.

Eligibility & pre-requisites

To succeed in this course, students should have the following foundational knowledge and skills:

Basic understanding of mathematics, especially:

  • Open to final-year and graduate students of BS/BE: Computer Science, IT, Information Systems, Software Engineering, Computer Engineering, AI, Data Science, and related fields.
  • Students who have completed 7th or 8th semester in the above programs are eligible to apply.
  • BS/BE graduates from Engineering, Mathematics, Statistics, and Physics with basic programming and database knowledge are encouraged to apply.
  • Basic understanding of programming (preferably Python) and databases (SQL basics such as SELECT, JOIN, WHERE) is required.
  • Comfort with basic statistics (averages, trends, distributions) and working with spreadsheets/CSV files is preferred.
  • Working professionals / freelancers from software development, databases, BI, or data analysis roles with hands-on experience in Python, SQL, or data tools are also eligible.

Introductory awareness of AI/Data Science concepts (recommended but not mandatory)

Basic knowledge of any programming language (Python is preferred but not mandatory)

Course outline

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