Data Science and Data Scientist

Understand Data, Tell Its Story, Build Smart Models

A visual, intermediate-but-simple journey into data science: what it is, how data scientists work, and how to explore, clean, visualize, and model data — then a gentle bridge into machine learning. Hands-on with real datasets. Adapted from Microsoft's Data Science for Beginners.

Intermediate43 modules4-6 monthsCurious learners and analysts moving into data science

Curriculum Modules

43 modules covering everything from fundamentals to advanced topics.

Capstone Project

Put everything together in a comprehensive final project that demonstrates your mastery. Includes real-world problem solving, documentation, and portfolio-ready deliverables.

View Capstone Details

Data Science and Data Scientist

Curriculum Modules

Module 1: What Is Data Science?

Module 2: The Data Scientist's Role & Mindset

Module 3: Data Ethics & Responsible Data Use

Module 4: Defining Data — Types & Sources

Module 5: Statistics Basics

Module 6: Probability Basics

Module 7: Relational Databases & SQL

Module 8: NoSQL & Non-Relational Data

Module 9: Python for Data Science

Module 10: Data Cleaning & Preparation

Module 11: Data Quality — Missing Values & Outliers

Module 12: Visualizing Quantities

Module 13: Visualizing Distributions

Module 14: Visualizing Proportions

Module 15: Visualizing Relationships

Module 16: Meaningful & Honest Visualizations

Module 17: Choosing the Right Chart

Module 18: The Data Science Lifecycle

Module 19: Analyzing Data

Module 20: Communicating & Data Storytelling

Module 21: Data Science in the Cloud

Module 22: Low-Code & AutoML

Module 23: Cloud ML Services

Module 24: Data Science in the Real World

Module 25: What Is Machine Learning?

Module 26: Features & Labels

Module 27: Supervised Learning — Regression

Module 28: Supervised Learning — Classification

Module 29: Unsupervised Learning & Clustering

Module 30: Training, Testing & Evaluation

Module 31: Overfitting & Underfitting

Module 32: Math Foundations (The Gentle Version)

Module 33: Deep Learning Basics

Module 34: Natural Language Processing

Module 35: Computer Vision

Module 36: Time Series

Module 37: MLOps Basics

Module 38: Tools of a Data Scientist

Module 39: Think Like a Data Scientist

Module 40: Practice Projects & Exercises

Module 41: Knowledge Check

Module 42: Glossary of Data Science Terms

Module 43: Learning Path & Next Steps

Capstone Project