Data-Science-For-Beginners/translations/pcm

Data Science for Beginners - A Curriculum

Azure Cloud Advocates for Microsoft dey happy to offer 10-week, 20-lesson curriculum wey dey all about Data Science. Each lesson get pre-lesson and post-lesson quizzes, written instructions to complete the lesson, solution, and assignment. Our project-based way of teaching go allow you learn while you build, na correct way for new skills to "stick".

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

🙏 Special thanks 🙏 go to our Microsoft Student Ambassador authors, reviewers and content contributors, especially 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 | Kannada | Korean | Lithuanian | Malay | Malayalam | 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 | Telugu | Thai | Turkish | Ukrainian | Urdu | Vietnamese

Prefer to Clone Locally?

This repository get 50+ language translations wey dey make di download size big well-well. To clone without translations, use sparse checkout:

git clone --filter=blob:none --sparse https://github.com/microsoft/Data-Science-For-Beginners.git
cd Data-Science-For-Beginners
git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'

Dis one go give you everything wey you need to complete di course with fast download.

If you want more translations wey dem dey support dey listed here

Join Our Community

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

You be student?

Start with these resources:

• Student Hub page For this page, you go find beginner resources, Student packs and even ways wey you fit get free cert voucher. This one na page wey you go like bookmark and dey check from time to time as we dey change content every month.
• Microsoft Learn Student Ambassadors Join global student ambassadors community, dis fit be your way enter Microsoft.

How to Start

📚 Documentation

• Installation Guide - Step-by-step setup instructions for beginners
• Usage Guide - Examples and common workflows
• Troubleshooting - Solutions to common wahala
• Contributing Guide - How to add your own work for this project
• For Teachers - Teaching guidance and classroom resources

👨‍🎓 For Students

Complete Beginners: You never sabi Data Science before? Start with our beginner-friendly examples! These simple examples wey fine-commented go help you understand the basics before you jump for the full curriculum. Students: to use this curriculum by yourself, fork the whole repo and do the exercises by yourself, start with the pre-lecture quiz. Then read the lecture and do the rest of the activities. Try create the projects by understanding the lessons instead of just copying solution code; but that code dey for the /solutions folders for each project-oriented lesson. Another way na to form study group with your friends and go through the content together. If you want study more, we recommend Microsoft Learn.

Quick Start:

1. Check the Installation Guide to set up your environment
2. Review the Usage Guide make you sabi how to wok with the curriculum
3. Start with Lesson 1 and continue sequentially
4. Join our Discord community for support

👩‍🏫 For Teachers

Teachers: we don put some suggestions for how to use this curriculum. We go like hear your feedback inside our discussion forum!

Meet di Team

Gif by Mohit Jaisal

🎥 Click di image wey dey above for video about di project an di people wey create am!

Pedagogy

We don choose two pedagogical tenets as we dey build dis curriculum: make sure say e dey project-based an e get frequent quizzes. By di time dis series end, students go don sabi basic principles of data science, including ethical concepts, data preparation, different ways to work with data, data visualization, data analysis, real-world use cases of data science, an more.

Plus, low-stakes quiz before class dey set di intention of di student to learn one topic, while second quiz after class dey make sure say dem still remember well. Dis curriculum e design to be flexible an fun, an you fit do am fully or partly. Di projects start small an dem go get more complex by di end of di 10 week cycle.

Find our Code of Conduct, Contributing, Translation guidelines dem. We welcome your constructive feedback!

Each lesson get:

• Optional sketchnote
• Optional supplemental video
• Pre-lesson warmup quiz
• Written lesson
• For project-based lessons, step-by-step guides on how to build di project
• Knowledge checks
• Challenge
• Supplemental reading
• Assignment
• Post-lesson quiz

Note about quizzes: All quizzes dey inside Quiz-App folder, total na 40 quizzes with three questions each. Dem dey linked from inside lessons, but you fit run quiz app locally or deploy am for Azure; follow di instruction inside quiz-app folder. Dem dey slowly dey localize.

🎓 Beginner-Friendly Examples

New to Data Science? We don create special examples directory with simple, well-commented 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 an find patterns
• 📈 Basic Visualization - Create charts an graphs
• 🔬 Real-World Project - Complete workflow from start to finish

Each example get detailed comments wey explain every step, e perfect for absolute beginners!

👉 Start with the examples 👈

Lessons

Data Science For Beginners: Roadmap - Sketchnote by @nitya

Lesson Number	Topic	Lesson Grouping	Learning Objectives	Linked Lesson	Author
01	Defining Data Science	Introduction	Learn di basic concepts behind data science an how e relate to artificial intelligence, machine learning, an big data.	lesson video	Dmitry
02	Data Science Ethics	Introduction	Data Ethics Concepts, Challenges & Frameworks.	lesson	Nitya
03	Defining Data	Introduction	How data dey classified an di common sources.	lesson	Jasmine
04	Introduction to Statistics & Probability	Introduction	Di mathematical techniques of probability an statistics to understand data.	lesson video	Dmitry
05	Working with Relational Data	Working With Data	Introduction to relational data an di basics of exploring an analyzing relational data with di Structured Query Language, wey dem also sabi as SQL (wey dem dey pronounce “see-quell”).	lesson	Christopher
06	Working with NoSQL Data	Working With Data	Introduction to non-relational data, di different types an basics of exploring an 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 inside interval.	lesson	Jen
11	Visualizing Proportions	Data Visualization	Visualizing discrete an grouped percentages.	lesson	Jen
12	Visualizing Relationships	Data Visualization	Visualizing connections and correlations between sets of data an their variables.	lesson	Jen
13	Meaningful Visualizations	Data Visualization	Techniques and guidance to make your visualizations valuable for effective problem solving and insights.	lesson	Jen
14	Introduction to the Data Science lifecycle	Lifecycle	Introduction 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 data in way wey go make am easy for decision makers to understand.	lesson	Jalen
17	Data Science in the Cloud	Cloud Data	Dis series of lessons introduce data science in the cloud and di benefits.	lesson	Tiffany and Maud
18	Data Science in the Cloud	Cloud Data	Training models using Low Code tools.	lesson	Tiffany and Maud
19	Data Science in the Cloud	Cloud Data	Deploying models with Azure Machine Learning Studio.	lesson	Tiffany and Maud
20	Data Science in the Wild	In the Wild	Data science driven projects for di real world.	lesson	Nitya

GitHub Codespaces

Follow dis steps to open dis sample inside Codespace:

1. Click di Code drop-down menu an select 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 inside container using your local machine an VSCode with di VS Code Remote - Containers extension:

1. If e be your first time to use developer container, make sure your system get di pre-reqs (like say Docker dey installed) for di getting started documentation.

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

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

Or open locally cloned or downloaded version of di repo:

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

Offline access

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

Note, notebooks no go render via Docsify, so if you need run notebook, make you do am separately inside VS Code running Python kernel.

Other Curricula

Our team dey produce other curricula! Check am out:

LangChain

Azure / Edge / MCP / Agents

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Generative AI Series

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Core Learning

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Copilot Series

Getting Help

You dey get wahala? Check our Troubleshooting Guide for how you fit solve common problems.

If you jam gbege or get any question about how to build AI apps. Join other people wey dey learn and programmers wey sabi for talks about MCP. E be like one supportive community wey you fit ask question anytime and dem dey share knowledge freely.

If you get product feedback or you see error while you dey build, com visit:

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Disclaimer: Dis dokument dem don translate am wit AI translation service wey dem dey call Co-op Translator. Even we dey try make everything correct, abeg make you sabi say machine translation fit get some mistake or wahala. Di original dokumentwey talk for e own language na di correct one. For important tins, e beta make person wey sabi do human translation do am. We no go responsible if pesin no understand well or if mistakes happen because of dis translation.