How to become a data scientist in 2024 - The only roadmap you need!

Start your exciting journey into Data Science with our easy-to-follow roadmap! No matter your background, this guide makes becoming a data scientist simple and understandable.

This roadmap is equipped with everything you need to propel yourself into the data science career. When I started out, I struggled, didn't know which path to take and what I need to learn. It's understandable given that data science is a multidisciplinary field and multiple disciplines and sciences intertwine.

Here's what is included:

• Introduction to data science, what it consists of, data scientist salary
• Introduction to Python - a complete roadmap of prerequisites in programming in Python. Learn data collection with BeautifulSoup and Scrapy
• Mathematics, probability and statistics foundations - learn the mathematical basis for data science
• Apply mathematical foundations in Python through Statistics, SciPy and various data visualizations you can make using Matplotlib and Seaborn
• Learn data analysis in Python - Pandas and NumPy
• Feature Engineering and Feature Encoding
• Machine learning roadmap using scikit-learn
• Neural networks foundations, introduction to different types of neural networks
• Deep learning roadmap with TensorFlow, Keras and PyTorch
• SQL Roadmap
• GANs Roadmap
• Git & Github foundations
• Cloud Computing Foundations for Data Scientists
• 50+ Project Ideas
• How to navigate the data science space amidst the AI Revolution and much more!

Why You Should Get this Roadmap?

This roadmap is a vital tool for aspiring data scientists, offering a structured and comprehensive guide to the field. It helps you navigate through complex topics, ensuring a well-rounded understanding of both theoretical and practical aspects of data science. By following this roadmap, you'll be equipped with the necessary skills and knowledge to excel in this dynamic and rapidly evolving field.

FAQ

1. What is a Data Science Roadmap? A Data Science Roadmap is a structured plan that outlines the key learning areas, skills, and knowledge necessary to become proficient in data science. It typically includes topics like programming, statistics, machine learning, data analysis, and domain-specific knowledge.
2. Can I use this Roadmap as a course? No, the roadmap is not a course itself; it's more of a guideline or syllabus to help structure your learning journey in data science. It outlines what you should learn but doesn't provide the detailed educational content or interactive learning experiences that a course offers.
3. Can you learn data science in less than 3 months? Learning the basics of data science in less than three months is possible, especially for those with a strong background in related fields like mathematics, statistics, or programming. However, gaining proficiency and mastering the field typically requires a longer, more in-depth study and practical experience.
4. Will AI replace data scientists? AI is unlikely to completely replace data scientists. While AI can automate some tasks, the role of a data scientist extends beyond what AI can currently achieve, especially in areas requiring creative problem-solving, domain expertise, ethical judgment, and interpretation of complex data​​​​​​​​​​​​​​​​.
5. How to use this roadmap? Use the roadmap as a guide to identify key areas and skills to focus on in your data science learning journey. It can help structure your studies, prioritize learning objectives, and track your progress. It's best used alongside courses, tutorials, and practical projects to apply the concepts you learn.

Note: This is not a course or a tutorial, it's a roadmap which you can use to keep up with your data science journey. This roadmap is ideal for data analysts, data scientists and machine learning engineers.