Starting a new journey of Relearning Data Science From The Ground Up 🧠
Not because I forgot, but because I want to understand better 💡
I’ll be documenting my journey here, one topic at a time 📚
#Data#DataScience#LearningInPublic
Free Certification Courses to Learn Data Science in 2025:
1. Python
🔗 https://t.co/dIF8TuaOLu
2. SQL
🔗 https://t.co/Ge4bFjars9
3. Statistics and R
🔗 https://t.co/41ya4HlxPS
4. Data Science: R Basics
🔗https://t.co/56xixoYoMg
5. Excel and PowerBI
🔗 https://t.co/oWULVWbQPg
6. Data Science: Visualization
🔗https://t.co/eQ7buwP4QU
7. Data Science: Machine Learning
🔗https://t.co/RYTIF3cocp
8. R
🔗https://t.co/aPvThGhFHw
9. Tableau
🔗https://t.co/94KUoem3Bf
10. PowerBI
🔗 https://t.co/gOV6kIG2kQ
11. Data Science: Productivity Tools
🔗 https://t.co/0fvxcgIQ4W
12. Data Science: Probability
🔗https://t.co/J0eC5jlOGX
13. Mathematics
🔗https://t.co/b62getHyo7
14. Statistics
🔗 https://t.co/Y82ToFqsFs
15. Data Visualization
🔗https://t.co/Yz8e2T6mdn
16. Machine Learning
🔗 https://t.co/VoHcNGJvfC
17. Deep Learning
🔗 https://t.co/TY3cjGHXdK
18. Data Science: Linear Regression
🔗https://t.co/5N2UOWUgxw
19. Data Science: Wrangling
🔗https://t.co/zTsUAAn1hE
20. Linear Algebra
🔗 https://t.co/UPNbNapSf0
21. Probability
🔗 https://t.co/UdOPPPyYJ8
22. Introduction to Linear Models and Matrix Algebra
🔗https://t.co/3hOAvinvhe
23. Data Science: Capstone
🔗 https://t.co/ac8w6CLS9T
24. Data Analysis
🔗 https://t.co/tKh5FYjMRM
25. IBM Data Science Professional Certificate
https://t.co/gFsFS3B6zu
26. Neural Networks and Deep Learning
https://t.co/SPyU710NvG
27. Supervised Machine Learning: Regression and Classification
https://t.co/ATOsYimRAJ
Dear Data Analyst/Scientist.
Read these books and you'll be miles ahead in your Data journey.
To get it:
1. Follow me (so I can DM you)
2. Like and retweet
3. Reply with "Data"
🔍 Exploratory Data Analysis (EDA) is your first step to understanding data. Discover distributions, spot outliers, and find relationships before modeling.
Let’s break down key EDA steps!
#EDA#DataScience
💡 Correlations matter! Use heatmaps and correlation matrices to see feature relationships and avoid multicollinearity in your models.
#FeatureEngineering
📉 Visualize with histograms, box plots, and scatter plots. Tools like Seaborn & Matplotlib make insights pop! Visuals reveal patterns numbers alone can’t.
#DataViz
Here is a list of some of my favorite data YouTubers and Streamers:
- Data science in the real world/sports @nickwan
- How to become a data scientist @KenJee_DS
- Practical data analytics @DaveOnData
- Data Science lifestyle @SeattleDataGuy
More 👇
https://t.co/lxnqAvnm1I