BEGINNER-LEVEL DATA SCIENCE SYLLABUS

Duration: 4–6 Weeks
Level: Beginner / No Prior Experience Needed
Tools: Python, Pandas, NumPy, Matplotlib

⭐ Module 1: Introduction to Data Science

What you learn:

• What is data science?
  
  

• Where is data science used?
  
  

• Types of data (Numerical, Categorical)
  
  

• Basic terms: Dataset, Features, Labels
  
  

Task:

• Explore a simple dataset (CSV file)
  
  

⭐ Module 2: Python Basics

Topics:

• Variables
  
  

• Data types
  
  

• Lists, Dictionaries
  
  

• Loops (for, while)
  
  

• Functions
  
  

Hands-on:

• Write simple Python programs
  
  

• Read a CSV file using Python
  
  

⭐ Module 3: NumPy Fundamentals

You learn:

• What is NumPy?
  
  

• Creating arrays
  
  

• Basic math operations
  
  

• Array slicing
  
  

Hands-on:

• Create arrays
  
  

• Perform array calculations
  
  

⭐ Module 4: Pandas for Data Handling

Topics:

• Read CSV files
  
  

• DataFrame basics
  
  

• Selecting rows/columns
  
  

• Filtering data
  
  

• Handling missing values
  
  

Hands-on:

• Load a student dataset
  
  

• Clean the data
  
  

• Find average, max, min
  
  

⭐ Module 5: Data Visualization (Matplotlib)

Topics:

• Line chart
  
  

• Bar chart
  
  

• Pie chart
  
  

• Scatter plot
  
  

Hands-on:

• Plot a chart of Marks vs Study Hours
  
  

• Create 5 different types of charts
  
  

⭐ Module 6: Beginner Machine Learning

You learn:

• What is machine learning?
  
  

• What is a model?
  
  

• What is training and testing?
  
  

• Basic algorithm: Linear Regression
  
  

Hands-on:

• Build a simple linear regression model
  
  

• Predict student marks
  
  

⭐ Module 7: Mini Project

Choose one:

📌 Project 1: Predict marks from study hours
📌 Project 2: Analyze sales data
📌 Project 3: Analyze student performance dataset

Includes:

• Load data
  
  

• Clean data
  
  

• Visualize data
  
  

• Apply linear regression
  
  

⭐ Bonus (Optional)

• What is Jupyter Notebook
  
  

• How to install Python
  
  

• How to use Google Colab
  
  

• How to find datasets (Kaggle)
  
  

🎯 Output After Course

By the end, the learner will be able to:

✔ Understand basic data science concepts
✔ Clean and analyze data using Pandas
✔ Visualize data with charts
✔ Build a simple machine learning model
✔ Complete a mini data project