Data Scientist Handbook 2025

Curated Data Science resources (Free & Paid) to help data scientists learn, grow, and break into the field

Note: For your convenience, if you see this symbol :heavy_dollar_sign: next to a resource, it means it is a paid resource. More information about this project can be found here

Table of Contents

1. 📚 Learning Data Science
   • YouTube Channels
   • Blogs
   • Newsletters
   • Podcasts
   • Books
   • Github Repos
2. 💼 Breaking into the Job Market
   • The Technical Interview
   • Building a Portfolio
   • Crafting a Resume
   • Job Market Insights
   • Courses & Mentorship
3. 🤝 Connecting with Others
   • Communities
   • Content Creators
   • Conferences

📚 Learning Data Science

YouTube Channels

Great YouTube channels with lots of free tutorials to help you learn data science, ideal for self-learners.

Core Data Science

• Data School: Practical data science tutorials and tips, perfect for beginners and those looking to refine their skills. Especially great for learning how to work with the pandas library.
• freeCodeCamp.org: Comprehensive tutorials on programming and data science, ideal for self-learners and career switchers.
• StatQuest with Josh Starmer: Simplifies complex statistical concepts and machine learning algorithms through engaging and easy-to-understand videos.
• Data Professor: Educational videos on data science, machine learning, and bioinformatics, aimed at helping you become a data professional.

AI & Machine Learning

• Two Minute Papers: Quick and engaging summaries of the latest AI research, making complex topics accessible.
• Sentdex: In-depth Python programming and machine learning tutorials, suitable for all skill levels.
• Boris Meinardus: Tutorials and insights on AI and machine learning with a focus on practical applications.

Data & Analytics

• Alex The Analyst: Real-world data analytics tutorials, especially useful for learning SQL.
• Luke Barousse: Data science projects and tutorials, focusing on practical applications and real-world use cases.
• Thu Vu Data Analytics: Educational videos on data analytics, machine learning tutorials, career advice, and insights to help viewers advance in the data analytics field.

Blogs

• Towards Data Science: A Medium publication that publishes well-written, informative articles on various data science topics.
• freeCodeCamp.org: Articles and tutorials covering a wide range of data science concepts, from basic to advanced.

Newsletters

• Neural Pulse: A 5-minute, human-curated newsletter delivering the best in AI, ML, and data science (twice a week).
• To Be a Data Scientist: A weekly newsletter exploring the journey to becoming a data scientist and providing practical insights to break into the field and stay relevant!
• Data Elixir: A weekly newsletter that curates the best data science news, resources, and tutorials from around the web.
• Data Science Weekly: A newsletter that provides a weekly roundup of data science news, articles, and tutorials.

Podcasts

• The TWIML AI Podcast: In-depth interviews with AI and machine learning experts, covering cutting-edge topics and industry trends.
• Data Skeptic: A podcast featuring interviews and discussions on data science, machine learning, and artificial intelligence.
• Data Topics: Go-to spot for relaxed discussions around tech, news, data, and society.
• The Data Coffee Break Podcast: From technical discussions to tangible impacts made by data, this podcast guides you in your journey to thrive in the field.

Books

• Practical Statistics for Data Scientists :heavy_dollar_sign:: A comprehensive guide to statistical methods and their application in data science.
• Python Data Science Handbook :heavy_dollar_sign:: Essential tools and techniques for data science using Python.
• Machine Learning Simplified :heavy_dollar_sign:: A clear and concise guide to understanding machine learning concepts and applications.
• Storytelling with Data :heavy_dollar_sign:: A guide to creating impactful data visualizations and telling compelling data-driven stories.
• Essential Math for Data Science :heavy_dollar_sign:: Master the math needed to excel in data science, machine learning, and statistics.

GitHub Repos

• AI Data Scientist Handbook 2026: A curated list of AI-native tools, workflows, and resources to help data scientists accelerate their careers in the age of AI.
• Awesome Generative AI Guide: A comprehensive hub for updates on generative AI research, interview materials, notebooks, and more!
• Free 6-Week SQL Roadmap for Data Science & Data Analytics: Roadmap to guide you through mastering SQL for Data Science in just 6 weeks.

💼 Breaking into the Job Market

The Technical Interview

Practicing for the coding part of the technical interview

• Dataford: All-in-one platform for your interview prep. Level-up your skills with Real Interview Questions from top companies, hands-on courses, and real case studies. Use code ANDRES40 to get 40% off yearly subscriptions.
• Interview Master (SQL): Practice with realistic problems from top tech companies. This tool combines realistic practice, AI-powered feedback, and structured learning to prepare you for any technical interview.
• Data Lemur (SQL): A collection of SQL interview questions to help you practice and improve your database querying skills.
• Ace the Data Science Interview :heavy_dollar_sign:: A comprehensive book with real interview questions and detailed answers to help you succeed in your data science interviews.
• Data Science Mock Interviews :heavy_dollar_sign:: Mock interview sessions with an experienced Data Scientist and ex-hiring manager to help you prepare for your next interview. Use code HANDBOOK20 for a discount.

Building a Portfolio

Resources to help you build a competitive Data Science portfolio

• Crafting a Data Science Portfolio That Will Actually Get You An Interview This 2024: Medium blog.
• datascienceportfol.io: Great website to showcase your portfolio projects for free and get inspiration from the community.
• How to Make a Data Science Portfolio With GitHub Pages (2024): YouTube video tutorial.
• Data Science Project Ideas (2025 Edition) :heavy_dollar_sign:: A curated collection of Data Science project ideas specifically designed to solve common business problems and catch the eye of hiring managers.

Crafting a Resume

• Applio :heavy_dollar_sign:: A tool built specifically to help data scientists align their applications, tailor their resumes, and prepare with confidence. Use coupon code HANDBOOK2025 to get 50% off.
• Enhance CV :heavy_dollar_sign:: A tool that helps you create modern-looking resumes with templates and guides.
• Free ATS-friendly Resumes Templates: ATS-friendly resume templates for data scientists, analysts, and AI engineers. Tailored to your background so your top skills stand out.
• 1:1 Resume/Portfolio Review :heavy_dollar_sign:: Personalized feedback on your resume and portfolio to help you land your dream job. Use code HANDBOOK20 for a discount.

Job Market Insights

• The Data Scientist Job Market in 2024: Article with insights on the data job market in 2024 based on research of 1,000 job postings.
• Data Job Market Dashboard: Regularly updated dashboard of the data job market, providing insights into in-demand skills for Data Scientist and Data Analyst roles.
• Glassdoor: Reviews, salary data, and interview experiences for companies and job roles in data science.

Courses and Mentorship

Getting one-on-one mentorship and general career guidance

• Andres Vourakis :heavy_dollar_sign:: Personalized mentorship and career guidance from an experienced data scientist and ex-hiring manager.
• Data Science Hire Ready :heavy_dollar_sign:: An accelerator program to help you gain a competitive advantage during your job search and land a data job quickly. Use coupon code student10 to get a student discount.
• Future Proof Data Science: AI Workflows Bootcamp :heavy_dollar_sign:: A cohort-based program that helps data scientists master AI workflows and automation to 10× productivity, stay relevant, and accelerate their careers.

🤝 Connecting with Others

Communities

Find great people to collaborate and exchange ideas

• Break Into Data (Discord): A community for aspiring and established data professionals to network, share knowledge, and empower each other to reach their goals.
• Data Science (Reddit): A subreddit for discussing all things data science, including career advice, project ideas, and industry news.
• Learn Data Science (Reddit): A supportive community for those learning data science, offering resources, project ideas, and peer support.
• DataTalks.club (Slack): Global community of data enthusiasts.

Content Creators

Data Scientists who share valuable insights and tutorials

All Around

• Carly Taylor: Machine Learning @ Call of Duty and rebel Data Scientist
• Aishwarya Naresh Reganti: Applied Science Tech Lead at the AWS Generative AI Innovation Center (GenAIIC)
• Eric Vyacheslav: AI/ML Engineer, ex-Google, and MIT Alumni
• Sundas Khalid: Content creator doing Data Science @ Google

Career guidance

• Sravya Madipalli: Senior Manager, Data Science (Ex-Microsoft)
• Dawn Choo: Data Scientist (ex-Meta, ex-Amazon) and interview coach.
• Andres Vourakis: Data Scientist (ex-hiring Manager), and career coach.
• Karun Tankachan: Senior Data Scientist @ Walmart and mentor.
• Mandy Liu Lead Data Scientist (ex-Meta), consultant and coach.

Conferences

United States

Europe

About

Even though there are hundreds of resources out there (too many to keep track of), I will try to limit them to a maximum of 5 per category to ensure you get the most valuable and relevant resources out there, plus, the whole point of this repository is to help you avoid getting overwhelmed by too many choices. This way you can focus less time researching and more time learning.

FAQs

1. How is curation done? Curation is based on thorough research, recommendations from people I trust, and my years of experience as a Data Scientist.
2. Are all resources free? Most resources here will be free, but I will also include paid alternatives if they are truly valuable to your career development. All paid resources include the symbol :heavy_dollar_sign:.
3. How often is the repository updated? I plan to come back here as often as possible to ensure all resources are still available and relevant and also to add new ones.

If you have questions or feedback send me a message through here. Enjoy!