📘 Course Overview

This course provides a thorough grounding in data science concepts, Python programming, statistical analysis, and machine learning. Perfect for beginners and professionals seeking a data-driven career.

• Duration: 50 Hours
• Mode: Online
• Level: Beginner to Advanced
• Tools: Python, Jupyter Notebooks, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn
• Certificate: Yes

🎯 Learning Outcomes

• Understand statistics and probability basics
• Write Python code for data analysis and visualization
• Build and evaluate machine learning models
• Work on real datasets and projects
• Prepare a portfolio to showcase your skills

📚 Course Modules

1. Introduction to Data Science (3 hrs)
   Concepts, tools, and project lifecycle
2. Python for Data Science (10 hrs)
   Basics, Pandas, NumPy, Jupyter Notebooks
3. Data Wrangling & Cleaning (7 hrs)
   Handling missing data, feature engineering
4. Exploratory Data Analysis (8 hrs)
   Visualization, statistical summaries
5. Statistics & Probability Basics (6 hrs)
   Distributions, hypothesis testing
6. Machine Learning Fundamentals (10 hrs)
   Supervised and unsupervised learning
7. Capstone Project (6 hrs)
   Real-world project and presentation

👥 Who Should Join?

• Students and fresh graduates
• IT professionals upskilling to Data roles
• Business analysts and professionals seeking data insights