Data-Science-For-Beginners/translations/pcm

Data Science for Beginners - A Curriculum

Azure Cloud Advocates dem for Microsoft dey happy to offer one 10-week, 20-lesson curriculum wey na all about Data Science. Every lesson get pre-lesson and post-lesson quizzes, written instructions to finish the lesson, one solution, and one assignment. Our project-based pedagogy dey allow you learn as you dey build, na verified 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 🙏 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?

Dis repository get over 50 language translation dem wey dey increase the download size 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 finish the course sharp-sharp.

If you wan get extra translation languages wey dem dey support, dem list dem here

Join Our Community

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

You be student?

Start with these resources:

• Student Hub page For dis page, you go find beginner resources, Student packs and even ways to get free cert voucher. Na one page wey you suppose bookmark and check every time as we dey change content at least every month.
• Microsoft Learn Student Ambassadors Join global community of student ambassadors, 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 problems dem
• Contributing Guide - How to contribute to this project
• For Teachers - Teaching guidance and classroom resources

👨‍🎓 For Students

Complete Beginners: New for data science? Start with our beginner-friendly examples! These simple examples with good comments go help you sabi the basics before you enter the full curriculum. Students: to use this curriculum on your own, fork the whole repo and complete the exercise by yourself, start with pre-lecture quiz. Then read the lecture and finish the rest activities. Try create the projects by understanding the lessons instead of just copying the solution code; but the code dey available for /solutions folders inside each project-based lesson. Another idea na to form study group with your 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 am sequencially
4. Join our Discord community for support

👩‍🏫 For Teachers

Teachers: we don put some suggestions on how to use this curriculum. We go happy to get your feedback for our discussion forum!

Meet the Team

Gif by Mohit Jaisal

🎥 Click di picture wey dey up dere for video about di project and di pipo wey create am!

Pedagogy

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

Plus, small quiz before class go set di mind of di student to learn di topic, and another quiz after class go make dem remember better. Dis curriculum na to make am flexible and fun and you fit do am complete or part. Di projects start small and e go get strong pass gidigba by di end of di 10 week cycle.

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

Each lesson get:

• Optional sketchnote
• Optional extra video
• Pre-lesson warmup quiz
• Written lesson
• For project-based lessons, step-by-step guide how to build di project
• Knowledge checks
• Challenge
• Extra reading
• Assignment
• Post-lesson quiz

Note about quizzes: All quizzes dey inside Quiz-App folder, total 40 quizzes wit three questions each. Dem link am from inside lessons, but quiz app fit run local or deploy for Azure; follow di instruction for the quiz-app folder. Dem dey localize dem steady steady.

🎓 Beginner-Friendly Examples

New to Data Science? We don create special examples directory wit simple, well-commented code to help you start well:

• 🌟 Hello World - Your first data science program
• 📂 Loading Data - Learn 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 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 wey dey behind 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	Defining Data	Introduction	How data dey classified and di common sources.	lesson	Jasmine
04	Introduction 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	Introduction to relational data and di basics of how to explore and analyze relational data wit di Structured Query Language, wey dem sabi as SQL (dem dey talk am “see-quell”).	lesson	Christopher
06	Working with NoSQL Data	Working With Data	Introduction to non-relational data, wetin different types of dem be and di basics of how to explore and analyze document databases.	lesson	Jasmine
07	Working with Python	Working With Data	Basics of how to use Python for data exploration wit libraries like Pandas. You need basic understanding of Python programming first.	lesson video	Dmitry
08	Data Preparation	Working With Data	Topics about ways dey clean and change data well to fit handle challenges like missing, inaccurate, or incomplete data.	lesson	Jasmine
09	Visualizing Quantities	Data Visualization	Learn how to use Matplotlib to see bird data 🦆	lesson	Jen
10	Visualizing Distributions of Data	Data Visualization	How to visualize observations and trends inside 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 data sets and im variables.	lesson	Jen
13	Meaningful Visualizations	Data Visualization	Techniques and advice to make your visualizations valuable for better problem solving and insights.	lesson	Jen
14	Introduction to the Data Science lifecycle	Lifecycle	Introduction to the data science lifecycle and di first step wen you acquire and extract data.	lesson	Jasmine
15	Analyzing	Lifecycle	Dis phase for data science lifecycle dey focus on techniques to analyze data.	lesson	Jasmine
16	Communication	Lifecycle	Dis phase for data science lifecycle dey focus on how to talk di insights from data, so decision makers fit understand better.	lesson	Jalen
17	Data Science in the Cloud	Cloud Data	Dis series of lessons introduce data science for cloud and di benefits.	lesson	Tiffany and Maud
18	Data Science in the Cloud	Cloud Data	How to train models wit Low Code tools.	lesson	Tiffany and Maud
19	Data Science in the Cloud	Cloud Data	How to deploy models wit Azure Machine Learning Studio.	lesson	Tiffany and Maud
20	Data Science in the Wild	In the Wild	Data science driven projects for 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 bottom for 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 and VSCode with di VS Code Remote - Containers extension:

1. If na your first time to dey use development container, make sure your system get all wetin e need first (like Docker installed) for di getting started documentation.

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

Note: Under di hood, dis one dey use Remote-Containers: Clone Repository in Container Volume... command to clone di source code inside Docker volume instead of local computer. Volumes na how we best dey keep container data safe.

Or open local cloned or downloaded version of di repository:

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

Offline access

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

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

Other Curricula

Our team dey produce other curricula! Check am:

LangChain

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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 face wahala? Check our Troubleshooting Guide for how to solve common wahala dem.

If you jam delay or get any question about how to build AI app dem. Join other learners and experienced developers for discussions about MCP. Na supportive community wey questions dey welcome and knowledge dey share freely.

If you get product feedback or errors while you dey build, make you visit:

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Disclaimer:
Dis document na im we dem don translate wit AI translation service Co-op Translator. Even though we dey try make am correct, abeg make you sabi say automated translations fit get some errors or mistakes. Di original document for im own language na di main correct source. If na serious tori, e better make human translator wey sabi do am translate am. We no go take blame if anybody misunderstand or misinterpret di translation.