The FREE Data Science Roadmap for 2024 - DSBoost #46
Whether you're a beginner or looking to sharpen your skills, this roadmap will guide you through the tools and skills you need in 2024 in Data Science.
1. Python & Pandas
Python is the most popular language in Data Science. You cannot go wrong with it. While R is fantastic for statistics, Python is more versatile, making it invaluable if you ever decide to pivot from Data Science.
After getting comfortable with Python, introduce yourself to Pandas. This powerful library is the go-to tool for data manipulation and analysis.
For a comprehensive introduction to Python, check out this tutorial.
And for Pandas use this playlist.
2. Data Visualization
It's not only about crafting visually appealing charts but also about understanding data cleaning, unleashing creativity, and getting used to coding best practices.
I usually suggest starting in your niche or with a topic you like. If you like football, you should recreate some scoring charts.
You will not find clean datasets for all charts, so it’s a good activity to practice data cleaning as well.
Matplotlib is the biggest data visualization library in Python, start with this tutorial.
3. SQL: The Language of Data
It’s a must for any serious data professional. SQL it the backbone for storing and retrieving data in most applications around us.
Dive into SQL with this comprehensive guide.
4. BI Tools
Business Intelligence (BI) tools are essential in translating complex data into actionable insights. This skill set is not just about creating visuals; it encompasses presentation, communication, and effective dashboarding techniques.
After mastering Power BI or Tableau, you're close to the Junior Data Analyst level. Start with this tutorial.
5. Machine Learning (ML)
The next level is to add some ML skills. Familiarize yourself with basic ML algorithms, and grasp the concepts of supervised and unsupervised learning.
You don’t need to do everything from scratch. Libraries like scikit-learn are awesome to start with.
An important note: You don’t need heavy math at this point. If you feel it’s a limitation of course you need to add the basics of statistics and math to your journey, but don’t start with it! Learn them as you go!
Begin your ML journey with this tutorial.
6. The Cloud
The cloud is revolutionizing data storage and computation. Understanding platforms like AWS is crucial for handling big data, deploying ML models, and ensuring scalable data solutions.
Check out this playlist to get started with cloud computing.
7. Niche down
After the basics, you can go deeper into some niche topics.
For example in Business / Finance some time-series knowledge is a must.
Here is a great roadmap:
Another fun topic is Natural Language Processing.
I am not sure if you have heard about ChatGPT in 2023 😊.
Learn about language models with this playlist.
Best wishes for 2024 and happy learning to all our readers!