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The Art of Learning Data Science (How to learn data science)

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Here's a video on how to learn data science in 2021. Whether you want to learn data science for leisure, to become a data scientist or to make sense of data, this video is for you. I will be sharing my best tips on how you can get started in learning data science. I have researched and distilled the essential best practices of what you can do to jump start your journey of learning data science.
⭕ Timeline
Introduction (0:00)
The Art of Learning Data Science is comprised of 4 steps: Plan, Learn, Build and Explain. (3:33)
👉Step 1 - Plan (4:14)
- Set learning goals (4:24)
- Create your own personal data science curriculum (5:57)
- Making a schedule (20:00)
- Consistency (20:30)
- Accountability (21:14)
👉Step 2 - Learn (22:09)
- Learning resources (22:20)
- Learn just enough to start building (25:17)
- Apply Pomodoro to manage learning time (27:56)
- Minimize stuck time (get stuck? move on and come back to it later) (28:23)
👉Step 3 - Building (29:29)
- Work on work-related projects (29:42)
- Work on weekend projects (30:09)
- Use public datasets or compile your own (e.g. web scraping) (30:29)
- Compete on Kaggle (30:35)
👉 Step 4 - Explain (30:47)
- Explain your model to others (31:26)
- Teach others (Feynman technique) (31:35)
- Mentor others (31:40)
- Write blog posts (31:46)
- Build well documented GitHub repository (31:50)
- Make YouTube videos (31:55)
- Give talks at meetups, conferences and podcasts (31:57)
- Draw infographics (32:16)
Other YouTube videos on learning data science from my friends and fellow YouTubers
--------------------
⭕ Playlist:
Check out our other videos in the following playlists.
#artoflearningdatascience #learndatascience #66daysofdata #datascience #machinelearning #python #bigdata #datamining #bigdata #datascienceworkshop #datasciencetutorial #ai #artificialintelligence #tutorial #dataanalytics #dataanalysis #dataprofessor #ai #datascientist
⭕ Timeline
Introduction (0:00)
The Art of Learning Data Science is comprised of 4 steps: Plan, Learn, Build and Explain. (3:33)
👉Step 1 - Plan (4:14)
- Set learning goals (4:24)
- Create your own personal data science curriculum (5:57)
- Making a schedule (20:00)
- Consistency (20:30)
- Accountability (21:14)
👉Step 2 - Learn (22:09)
- Learning resources (22:20)
- Learn just enough to start building (25:17)
- Apply Pomodoro to manage learning time (27:56)
- Minimize stuck time (get stuck? move on and come back to it later) (28:23)
👉Step 3 - Building (29:29)
- Work on work-related projects (29:42)
- Work on weekend projects (30:09)
- Use public datasets or compile your own (e.g. web scraping) (30:29)
- Compete on Kaggle (30:35)
👉 Step 4 - Explain (30:47)
- Explain your model to others (31:26)
- Teach others (Feynman technique) (31:35)
- Mentor others (31:40)
- Write blog posts (31:46)
- Build well documented GitHub repository (31:50)
- Make YouTube videos (31:55)
- Give talks at meetups, conferences and podcasts (31:57)
- Draw infographics (32:16)
Other YouTube videos on learning data science from my friends and fellow YouTubers
--------------------
⭕ Playlist:
Check out our other videos in the following playlists.
#artoflearningdatascience #learndatascience #66daysofdata #datascience #machinelearning #python #bigdata #datamining #bigdata #datascienceworkshop #datasciencetutorial #ai #artificialintelligence #tutorial #dataanalytics #dataanalysis #dataprofessor #ai #datascientist
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