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Full Stack Data Science and AI Data Science

Full Stack Data Science and AI

Master Python, statistics, data analytics, machine learning, and AI to build intelligent, data-driven applications.

This comprehensive course covers the complete data science lifecycle, from data collection and analysis to machine learning, generative AI, and deployment. Students learn Python programming, SQL, statistics, data visualization, predictive modeling, deep learning fundamentals, and AI application development. Through practical assignments and real-world projects, learners develop skills to transform raw data into actionable insights and build intelligent solutions for business problems.

Duration
6 Months
Level
Beginner
Format
Online
Language
English, Hindi
Time commitment
8–10 hours per week
Course code
FSDSAI-101

Who this course is for

Students, graduates, aspiring data scientists, data analysts, software developers, engineers, business analysts, and professionals interested in data analytics, machine learning, and artificial intelligence careers.

What you will learn

  • - Write Python programs for data processing and analysis.
  • - Apply statistics and probability to real-world datasets.
  • - Clean, transform, and analyze structured data.
  • - Query databases using SQL.
  • - Create visualizations and interactive analytical dashboards.
  • - Perform exploratory data analysis and identify trends.
  • - Build machine learning models for prediction and classification.
  • - Evaluate model performance using appropriate metrics.
  • - Understand deep learning and neural network fundamentals.
  • - Apply natural language processing and generative AI concepts.
  • - Develop AI-powered data applications using model APIs.
  • - Deploy data science and machine learning solutions.
  • - Communicate findings through reports and data storytelling.

Course curriculum

Module 1: Python Programming Fundamentals Module 2: Mathematics and Statistics Module 3: SQL and Database Management Module 4: Data Analysis with Python Module 5: Data Visualization and Business Intelligence Module 6: Machine Learning Module 7: Machine Learning Evaluation Module 8: Deep Learning and NLP Module 9: Generative AI and LLM Applications Module 10: Deployment and MLOps Fundamentals

Prerequisites

- Basic computer and internet knowledge. - School-level mathematics is recommended. - No previous professional data science experience required. - Basic programming knowledge is helpful but not mandatory. - A laptop or desktop with internet access. - Access to selected AI services may require paid API credits.

Projects and practical work

- Project 1: Sales data analysis and business insights dashboard. - Project 2: Customer segmentation using machine learning. - Project 3: House price prediction using regression. - Project 4: Customer churn prediction and model evaluation. - Project 5: Sentiment analysis of customer reviews. - Project 6: Build a document-based AI question-answering assistant using RAG. - Final Project: Develop an end-to-end data science solution that includes data preparation, exploratory analysis, machine learning, visualization, and deployment of an AI-powered application.

Certificate

Certificate of Course Completion Students who successfully complete the required modules, practical assignments, assessments, and capstone project will receive an institute-issued Full Stack Data Science and AI Course Completion Certificate.