Data Science with Gen AI course in Coimbatore

From Excel & SQL to ML, Deep Learning and GenAI.

Syllabus

1. Module 1: Foundations - Data Science Landscape and Lifecycle, Environment Setup
2. Module 2: Excel for Data Analysis - Excel Basics, Data Entry and Formatting, Formulas and Functions, Lookup and Logical Functions, Data Cleaning and Power Query, Pivot Tables and Pivot Charts, Charts and Excel Dashboards, Advanced Excel, Excel Project
3. Module 3: SQL for Data Analysis - Database Concepts and Setup, Querying Data, Aggregates and Grouping, Joins, Set Operations and Subqueries, CTEs and Advanced Subqueries, Window Functions, DDL, DML, Constraints and Normalisation, Views, Indexes and Optimisation, SQL Project
4. Module 4: Power BI - Power BI Introduction and Data Connection, Power Query Transformations, Data Modelling, DAX Basics, DAX Time Intelligence and Advanced DAX, Visuals and Report Design, Power BI Service, Publishing and Security, Power BI Project
5. Module 5: Python for Data Analysis - Python Basics, Control Flow and Loops, Functions, Modules and Comprehensions, Data Structures, File Handling, Errors and OOP Basics, NumPy: Arrays and Operations, NumPy: Broadcasting and Simulation, Pandas: Series and DataFrames, Pandas: Data Cleaning, Pandas: GroupBy, Merge and Reshape, Pandas: Time Series and Advanced, Matplotlib, Seaborn, EDA Project, Data Acquisition: APIs and Web Scraping, Python Project
6. Module 6: Looker Studio & Tableau - Looker Studio Basics, Looker Studio Advanced, Dashboard Design and Data Storytelling, Tableau Basics, Tableau Advanced, Tableau Dashboard Design and Publishing
7. Module 7: Statistics and Math for ML - Descriptive Statistics, Probability, Distributions and Central Limit Theorem, Sampling, Confidence Intervals and Hypothesis Testing
8. Module 8: Machine Learning - ML Introduction and Workflow, Preprocessing and Feature Engineering, Linear Regression, Regularisation and Regression Metrics, Logistic Regression, Classification Metrics and Class Imbalance, KNN and Naive Bayes, Decision Trees, Random Forest and Bagging, Boosting, Support Vector Machines, Clustering and PCA, Model Selection, Tuning and Pipelines, ML Projects
9. Module 9: Deep Learning - Neural Network Fundamentals, Keras, TensorFlow and PyTorch Basics, Training Deep Networks, Convolutional Neural Networks, Computer Vision: Transfer Learning, RNN, LSTM and Time-Series Forecasting, Deep Learning Project
10. Module 10: Natural Language Processing - Text Preprocessing, Bag of Words and TF-IDF, Word Embeddings and Text Classification, Transformers and Attention, Hugging Face for NLP, NLP Project
11. Module 11: Generative AI - LLM Fundamentals, Prompt Engineering, LLM APIs and Local Models, Embeddings and Vector Databases, RAG: Build a Pipeline, RAG: Evaluation and Improvement, Fine-Tuning Walkthrough, AI Agents: Tools and Function Calling, AI Agents: LangGraph, MCP and Multi-Agent, GenAI Apps and Responsible AI
12. Module 12: Deployment and MLOps - Deploying Models with FastAPI and Streamlit Cloud, Docker and Cloud Deployment, MLOps Basics
13. Module 13: Capstone and Career Guidance - Capstone Strategy, Data and Modelling, Capstone Build and Deploy, Capstone Documentation, Portfolio and Case Study, Presentation and Career Guidance

Tools

Excel, Google Sheets, MySQL, Power BI, Looker Studio, Tableau, Python, NumPy, Pandas, Matplotlib, Seaborn, SciPy, Statsmodels, scikit-learn, XGBoost, LightGBM, TensorFlow, Keras, PyTorch, Hugging Face Transformers, Streamlit, LangChain, LangGraph, MLflow, Ollama, ChatGPT, Claude, Gemini, Copilot, Perplexity, Cursor, AI2SQL, Text2SQL.ai, Julius, Mockaroo

Projects

• Capstone: End-to-End BI to AI Product: One real business problem taken from raw data through SQL/Excel cleaning, Python analysis, a BI dashboard, a trained ML or GenAI model and a deployed, documented application.
• Customer Churn Prediction: A full ML classification pipeline: preprocessing, model comparison, tuning and evaluation.
• Image Classifier with Transfer Learning: A fine-tuned CNN on a public image dataset using a pretrained backbone.
• Product Review Analyser (NLP): Sentiment, topic and summary extraction from real customer reviews using Hugging Face pipelines.
• Document Q&A Bot (RAG): A retrieval-augmented chatbot that answers questions from uploaded documents.
• Deployed ML Model API: A trained model served through FastAPI, containerised and deployed to a free cloud tier.

Career roles

Data Analyst, Junior Data Scientist, BI Analyst, Machine Learning Engineer, GenAI / AI Engineer, Data Science Trainee

Download the Data Science with Gen AI syllabus (PDF)

FAQs

Which is the best data science course in Coimbatore for freshers?

Vinsup Skill Academy's Data Science with Gen AI is a 200-hour classroom and online program at our Ganapathy, Coimbatore campus. It starts from Excel and SQL and builds up to Machine Learning, Deep Learning, NLP and Generative AI, with five mini projects, an end-to-end capstone, internship and placement support.

Does this data science course cover Generative AI, RAG and AI agents?

Yes. Module 11 is fully dedicated to Generative AI: LLM fundamentals, prompt engineering, LLM APIs and local models (Ollama), embeddings and vector databases, building and evaluating RAG pipelines, a fine-tuning walkthrough, and AI agents with function calling, LangGraph and MCP.

Do I need coding knowledge to join?

No. Python, SQL and statistics are taught from scratch. The course is designed for students, fresh graduates and career switchers, including learners from non-IT backgrounds.

What tools will I learn?

Excel, Google Sheets, MySQL, Power BI, Looker Studio, Tableau, Python, NumPy, Pandas, Matplotlib, Seaborn, scikit-learn, XGBoost, LightGBM, TensorFlow, Keras, PyTorch, Hugging Face, LangChain, LangGraph, Streamlit, MLflow and Ollama, plus AI assistants like ChatGPT, Claude, Gemini, Copilot and Cursor.

What projects will I build?

A capstone that takes one business problem from raw data to a deployed AI application, plus mini projects in churn prediction, image classification with transfer learning, NLP review analysis, a RAG document Q&A bot and a deployed FastAPI model.

Is placement support included?

Yes. Through our Job Readiness Program (JRP) and Interview Opportunity Program (IOP) you get soft-skills and aptitude training, portfolio building, internship, AI mock interviews, resume support and guaranteed interview opportunities.

What jobs can I get after this course?

Data Analyst, Junior Data Scientist, BI Analyst, Machine Learning Engineer (entry), GenAI / AI Engineer (entry) and Data Science Trainee roles.

Where are the classes held?

Classroom sessions are held at Vinsup Skill Academy, 148 Gopalasamy Koil Street, Sridevi Nagar, Ganapathy, Coimbatore 641006. Online sessions are also available.

Vinsup Skill Academy, 148, A B Gopalsamy Koil Street, Sridevi Nagar, Ganapathy, Coimbatore, Tamil Nadu 641006. Phone: +91-8248826374