Data Science & Generative AI Course
Turn data into opportunities. Learn how to analyze, interpret, and visualize data using industry-relevant tools, expert mentorship, and practical training.
Start date: 7th Sept
Start date: 28th Sept
- Batch Mode: Classroom or Online
- Languages: English/ Hindi
Industry-Ready
Curriculum perfectly mapped to match current requirements across data modern architectures.
Practitioner Driven
Hands-on assignments, complete sandbox structures and active real-world data scenario mockups.
Placement Focus
End-to-end guidance from dedicated mock runs, profile upgrades to corporate networks.
Explore the Program Curriculum
A comprehensive multi-module approach built seamlessly from core primitives to deployment layers.
Fundamentals of Analytics
- Business Intelligence & Data Warehouse concepts
- BI / DW Lifecycle
- Business Owner & Consultant roleplay
- Data Modeling (Dimensional Modeling )
- Data Visualization Workshop
- Analytics Demo
- Career Opportunities discussion & guidance
- Steps to be carried out
Excel Analytics – Spreadsheet Analytics
- Fundamentals and Excel interface
- Data population and error handling
- Excel features / Data quality
- Data Protection
- Excel functions
- Pivoting
- Charts
Database and SQL
- Database Concepts
- Standard SQL Query Writing
- Advanced SQL Query Writing Techniques
Python Programming
- Setting Python in Windows
- Introduction to print()
- Variable and Data Type
- Enumerators, operators, building basic expressions
- More print(), input()
- String data type indexing and slicing
- Program flow controls
- Loops
- Data structures – List, Dictionary, Tuple, Set
- Introduction to functions
- Exception Handling
- Object Oriented Programming concepts
- Reading from text files and writing to text files, .csv files
- URL Libraries
AI ML using python
- NumPy
- Dataframes using pandas library
- Datasets
- Introduction to Machine Learning
- Classification
- Dimensionality
- Types Of Supervised Learning
- Probability
- Decision Trees
- Feature Selection
- Sampling And Evaluation
- Linear Regression
- Logistic Regression
- Clustering - KMeans
Gen AI
- Generative AI - Introduction
- Natural Language Processing (NLP)
- Large Language Models (LLMs)
- Basic Approaches of NLP
- Word Embedding
- Introduction to BERT
- Hugging Face Repository
- Building a User Interface
Key Features of the Program
Industry-Aligned
Built side-by-side with working industry guidelines.
Experienced Faculty
Mentorship delivered by industry-seasoned consultants.
Practitioner Approach
Deeper insights via realistic workflow simulations.
Course Certification
Validated course-completion document verification.
Profile Overhauls
Resume restructuring and professional optimizations.
Mock Interview Drill
Extensive practice runs with actionable grading rules.
Placement Assistance
Dedicated assistance to manage corporate hiring pathways.
Internship Options
Opportunities to work on production infrastructure pipelines.
Job Roles
Who Should Enroll?
Our teaching approach is highly adaptable and learner centric. We have successfully delivered this course to a wide audience—ranging from a 6th-grade student to an 82-year-old professional— proving that with the right guidance, data science can be learned by anyone, regardless of age or background.