Data-Science-For-Beginners/translations/pcm

Data Science for Beginners - Curriculum

Azure Cloud Advocates for Microsoft don bring beta 10-week, 20-lesson curriculum wey dey teach Data Science. Each lesson get quiz before and after, written instructions to complete am, solution, and assignment. Dis project-based way of learning go help you sabi well as you dey build.

Big thanks to our authors: Jasmine Greenaway, Dmitry Soshnikov, Nitya Narasimhan, Jalen McGee, Jen Looper, Maud Levy, Tiffany Souterre, Christopher Harrison.

🙏 Special thanks 🙏 to our Microsoft Student Ambassador authors, reviewers and contributors, like Aaryan Arora, Aditya Garg, Alondra Sanchez, Ankita Singh, Anupam Mishra, Arpita Das, ChhailBihari Dubey, Dibri Nsofor, Dishita Bhasin, Majd Safi, Max Blum, Miguel Correa, Mohamma Iftekher (Iftu) Ebne Jalal, Nawrin Tabassum, Raymond Wangsa Putra, Rohit Yadav, Samridhi Sharma, Sanya Sinha, Sheena Narula, Tauqeer Ahmad, Yogendrasingh Pawar , Vidushi Gupta, Jasleen Sondhi

Data Science For Beginners - Sketchnote by @nitya

🌐 Multi-Language Support

Supported via GitHub Action (Automated & Always Up-to-Date)

Arabic | Bengali | Bulgarian | Burmese (Myanmar) | Chinese (Simplified) | Chinese (Traditional, Hong Kong) | Chinese (Traditional, Macau) | Chinese (Traditional, Taiwan) | Croatian | Czech | Danish | Dutch | Estonian | Finnish | French | German | Greek | Hebrew | Hindi | Hungarian | Indonesian | Italian | Japanese | Korean | Lithuanian | Malay | Marathi | Nepali | Nigerian Pidgin | Norwegian | Persian (Farsi) | Polish | Portuguese (Brazil) | Portuguese (Portugal) | Punjabi (Gurmukhi) | Romanian | Russian | Serbian (Cyrillic) | Slovak | Slovenian | Spanish | Swahili | Swedish | Tagalog (Filipino) | Tamil | Thai | Turkish | Ukrainian | Urdu | Vietnamese

If you wan add more translations, check here

Join Our Community

We get Discord learn with AI series wey dey happen, learn more and join us for Learn with AI Series from 18 - 30 September, 2025. You go learn tips and tricks for using GitHub Copilot for Data Science.

You be student?

Start with dis resources:

• Student Hub page Dis page get beginner resources, Student packs and even ways to get free cert voucher. Bookmark am and dey check am as we dey change content monthly.
• Microsoft Learn Student Ambassadors Join global community of student ambassadors, e fit be your way into Microsoft.

How to Start

📚 Documentation

• Installation Guide - Step-by-step setup instructions for beginners
• Usage Guide - Examples and common workflows
• Troubleshooting - Solutions to common issues
• Contributing Guide - How to contribute to dis project
• For Teachers - Teaching guidance and classroom resources

👨‍🎓 For Students

Complete Beginners: You dey new to data science? Start with our beginner-friendly examples! Dis simple, well-commented examples go help you understand the basics before you enter the full curriculum. Students: If you wan use dis curriculum by yourself, fork the repo and complete the exercises by yourself, start with pre-lecture quiz. Then read the lecture and complete the activities. Try to create the projects by understanding the lessons instead of copying the solution code; but the code dey available for /solutions folders for each project-oriented lesson. Another idea na to form study group with friends and go through the content together. For more study, we recommend Microsoft Learn.

Quick Start:

1. Check the Installation Guide to set up your environment
2. Review the Usage Guide to learn how to work with the curriculum
3. Start with Lesson 1 and work through sequentially
4. Join our Discord community for support

👩‍🏫 For Teachers

Teachers: we don add some suggestions on how to use dis curriculum. We go like your feedback for our discussion forum!

Meet the Team

Gif by Mohit Jaisal

🎥 Click the image above for video about the project and the people wey create am!

Pedagogy

We don pick two main teaching principles wen we dey use build dis curriculum: make sure say e dey project-based and e get plenty quizzes. By di end of dis series, students go sabi di basic principles of data science, including ethical concepts, how to prepare data, different ways to work with data, data visualization, data analysis, real-world examples of data science, and plenty more.

Plus, small quiz before class dey help set di student mind to learn di topic, and di second quiz after class go help dem remember wetin dem learn. Dis curriculum dey flexible and e dey fun, and you fit do am complete or just some parts. Di projects go start small and go dey more complex as di 10-week cycle dey go.

Check our Code of Conduct, Contributing, and Translation guidelines. We go like hear your constructive feedback!

Each lesson get:

• Optional sketchnote
• Optional extra video
• Warmup quiz before lesson
• Written lesson
• For project-based lessons, step-by-step guide on how to build di project
• Knowledge checks
• One challenge
• Extra reading
• Assignment
• Post-lesson quiz

About quizzes: All di quizzes dey inside di Quiz-App folder, total of 40 quizzes wey get three questions each. Dem dey linked inside di lessons, but you fit run di quiz app for your computer or deploy am to Azure; follow di instruction for di quiz-app folder. Dem dey localize di quizzes small small.

🎓 Beginner-Friendly Examples

You new to Data Science? We don create one special examples directory wey get simple, well-explained code to help you start:

• 🌟 Hello World - Your first data science program
• 📂 Loading Data - Learn how to read and explore datasets
• 📊 Simple Analysis - Calculate statistics and find patterns
• 📈 Basic Visualization - Create charts and graphs
• 🔬 Real-World Project - Complete workflow from start to finish

Each example get detailed comments wey explain every step, e go perfect for people wey just dey start!

👉 Start with the examples 👈

Lessons

Data Science For Beginners: Roadmap - Sketchnote by @nitya

Lesson Number	Topic	Lesson Grouping	Learning Objectives	Linked Lesson	Author
01	Wetin Be Data Science	Introduction	Learn di basic concepts of data science and how e relate to artificial intelligence, machine learning, and big data.	lesson video	Dmitry
02	Data Science Ethics	Introduction	Data Ethics Concepts, Challenges & Frameworks.	lesson	Nitya
03	Wetin Be Data	Introduction	How dem dey classify data and di common sources.	lesson	Jasmine
04	Intro to Statistics & Probability	Introduction	Di mathematical techniques of probability and statistics to understand data.	lesson video	Dmitry
05	Working with Relational Data	Working With Data	Intro to relational data and di basics of exploring and analyzing relational data with SQL (Structured Query Language).	lesson	Christopher
06	Working with NoSQL Data	Working With Data	Intro to non-relational data, di different types and di basics of exploring and analyzing document databases.	lesson	Jasmine
07	Working with Python	Working With Data	Basics of using Python for data exploration with libraries like Pandas. Foundational understanding of Python programming dey recommended.	lesson video	Dmitry
08	Data Preparation	Working With Data	Topics on data techniques for cleaning and transforming data to handle challenges of missing, inaccurate, or incomplete data.	lesson	Jasmine
09	Visualizing Quantities	Data Visualization	Learn how to use Matplotlib to visualize bird data 🦆	lesson	Jen
10	Visualizing Distributions of Data	Data Visualization	Visualizing observations and trends within an interval.	lesson	Jen
11	Visualizing Proportions	Data Visualization	Visualizing discrete and grouped percentages.	lesson	Jen
12	Visualizing Relationships	Data Visualization	Visualizing connections and correlations between sets of data and their variables.	lesson	Jen
13	Meaningful Visualizations	Data Visualization	Techniques and guidance for making your visualizations valuable for effective problem solving and insights.	lesson	Jen
14	Intro to di Data Science lifecycle	Lifecycle	Intro to di data science lifecycle and di first step of acquiring and extracting data.	lesson	Jasmine
15	Analyzing	Lifecycle	Dis phase of di data science lifecycle focus on techniques to analyze data.	lesson	Jasmine
16	Communication	Lifecycle	Dis phase of di data science lifecycle focus on presenting di insights from di data in a way wey decision makers go understand.	lesson	Jalen
17	Data Science in di Cloud	Cloud Data	Dis series of lessons introduce data science in di cloud and di benefits.	lesson	Tiffany and Maud
18	Data Science in di Cloud	Cloud Data	Training models using Low Code tools.	lesson	Tiffany and Maud
19	Data Science in di Cloud	Cloud Data	Deploying models with Azure Machine Learning Studio.	lesson	Tiffany and Maud
20	Data Science in di Wild	In the Wild	Data science driven projects in di real world.	lesson	Nitya

GitHub Codespaces

Follow dis steps to open dis sample for Codespace:

1. Click di Code drop-down menu and select di Open with Codespaces option.
2. Select + New codespace for di bottom of di pane. For more info, check di GitHub documentation.

VSCode Remote - Containers

Follow dis steps to open dis repo for container using your local machine and VSCode with di VS Code Remote - Containers extension:

1. If na your first time to use development container, make sure say your system meet di pre-reqs (e.g. get Docker installed) for di getting started documentation.

To use dis repository, you fit open di repository for isolated Docker volume:

Note: For di background, dis go use di Remote-Containers: Clone Repository in Container Volume... command to clone di source code for Docker volume instead of di local filesystem. Volumes na di preferred way to keep container data.

Or open a locally cloned or downloaded version of di repository:

• Clone dis repository to your local filesystem.
• Press F1 and select di Remote-Containers: Open Folder in Container... command.
• Select di cloned copy of dis folder, wait make di container start, and try things out.

Offline access

You fit run dis documentation offline by using Docsify. Fork dis repo, install Docsify for your local machine, then for di root folder of dis repo, type docsify serve. Di website go dey served for port 3000 for your localhost: localhost:3000.

Note, notebooks no go render via Docsify, so when you need to run notebook, do am separately for VS Code wey dey run Python kernel.

Other Curricula

Our team dey produce other curricula! Check dem out:

Azure / Edge / MCP / Agents

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Generative AI Series

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Core Learning

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Copilot Series

How You Go Fit Get Help

You dey face wahala? Check our Troubleshooting Guide to see solution for common problems.

If you dey stuck or you get any question about how to build AI apps, join other learners and developers wey sabi MCP. Na one kind supportive community wey dey welcome questions and dey share knowledge freely.

If you get feedback about product or you dey see error when you dey build, visit:

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Disclaimer:
Dis docu don dey translate wit AI translation service Co-op Translator. Even though we dey try make e accurate, abeg sabi say automatic translation fit get mistake or no correct well. Di original docu for im native language na di main correct source. For important information, e better make una use professional human translation. We no go fit take blame for any misunderstanding or wrong interpretation wey fit happen because of dis translation.