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AI-Powered Master Certificate in Data Science Professional

An industry-focused AI-powered master program designed to develop end-to-end Data Science professionals. Learn Python, SQL, data engineering, mathematics and statistics, exploratory data analysis, machine learning, Generative AI, LLMs, RAG, AI agents, cloud deployment, and MLOps while building real-world analytics and AI applications.

5 Months Duration
200 Hours
Online / Offline
Weekday Batch · Weekend Batch
PythonJupyter NotebookAnacondaNumPyPandasSQLMySQLPostgreSQLMatplotlibSeabornPlotlyPower BIScikit-learnOpenAI APIGemini APIClaudeLangChainChromaDBFAISSFastAPIStreamlitDockerAWSGitGitHub

Course Overview

An industry-focused AI-powered master program designed to develop end-to-end Data Science professionals. Learn Python, SQL, data engineering, mathematics and statistics, exploratory data analysis, machine learning, Generative AI, LLMs, RAG, AI agents, cloud deployment, and MLOps while building real-world analytics and AI applications. This course is designed to be practical and project-focused, ensuring you gain real, applicable skills rather than just theoretical knowledge.

Who Is This Course For?

Engineering students
Computer Science & IT graduates
Statistics & Mathematics students
Aspiring Data Scientists
Working professionals
Data Analysts transitioning into AI/ML

Prerequisites

  • Basic computer knowledge
  • Basic mathematics recommended
  • No prior data science experience required
  • Laptop with Python development environment recommended

What You Will Learn

Develop strong Python programming and data processing skills
Work with relational databases and advanced SQL analytics
Build ETL pipelines and analytical data marts
Apply mathematics and statistics to real-world data science problems
Perform EDA, feature engineering, and business data visualization
Develop and evaluate machine learning models using Scikit-learn
Build LLM, RAG, semantic search, and AI-agent applications
Deploy machine learning and AI applications using FastAPI, Streamlit, Docker, and cloud platforms
Build enterprise-level data science projects for a professional portfolio

Complete Syllabus

  • Python Environment Setup
  • VS Code, Jupyter & Anaconda
  • Variables & Data Types
  • Operators
  • Control Statements
  • Functions
  • Object-Oriented Programming
  • Modules & Packages
  • NumPy Fundamentals
  • Pandas DataFrames & Series
  • Data Cleaning
  • Missing Value Handling
  • CSV, Excel & JSON Files
  • Exploratory Data Processing
  • Exception Handling
  • Logging
  • Mini Project: Sales Data Processing System

Projects in This Course

Sales Data Processing System
Retail Data Warehouse
Executive Analytics Dashboard
Customer Churn Prediction System
AI Business Intelligence Assistant
ML Prediction API
AI-Powered Decision Intelligence Platform

Career Paths After This Course

Data Scientist
Machine Learning Engineer
Data Analyst
AI Engineer
Data Engineer
ML Operations Engineer

Course FAQs