This video reveals all the secrets, full study plan and all the tips & tricks on how to quickly and successfully become a Data Scientist in 2023.
DATA SCIENCE ROADMAP:
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MINIMUM AMOUNT OF KNOWLEDGE REQUIRED TO APPLY FOR A DS POSITION:
Step 1️⃣
Get to know python - https://tinyurl.com/5yhhw6e8
Step 2️⃣
Some more python (OOP) - https://tinyurl.com/58wkzhn7
Step 3️⃣
Data Science basics - https://tinyurl.com/4u6hrypa
Step 4️⃣
Participate in 2 Kaggle competitions. I advice starting with these 2:
https://www.kaggle.com/c/home-credit-...
https://www.kaggle.com/competitions/s...
My notebooks for these competitions (they are in R, so you can use them as a general reference):
https://www.kaggle.com/code/danilz/me...
https://www.kaggle.com/code/danilz/ex...
Step 5️⃣
Competitive Data Science course materials:
video lectures: https://www.bilibili.com/video/BV1174...
programming assignments: https://github.com/Brandon-HY-Lin/cou...
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Further study materials broken down into subjects:
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BEST NEURAL NETWORKS EDUCATION PROGRAM (in sequence)
Course 1 (NN&DL): https://imp.i384100.net/NeuralNetworks1
Course 2 (NN hyperparameters): https://imp.i384100.net/NeuralNetworks2
Course 3 (StructuingMLProjects): https://imp.i384100.net/NeuralNetworks3
Course 4 (CNN): https://imp.i384100.net/NeuralNetworks4
Course 5 (Sequence Models): https://imp.i384100.net/NeuralNetworks5
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TIME SERIES ANALYSIS & PREDICTION
Great course from deeplearning.ai:
https://imp.i384100.net/time_sereis_c...
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NATURAL LANGUAGE PROCESSING
Introductory course (good starting course): https://tinyurl.com/mu9twwjz
Comprehensive & exhaustive specialisation: https://imp.i384100.net/a1bgJj
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DATA VISUALISATION
From beginner to pro: https://tinyurl.com/yd6mh6bj
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WORKING WITH BIG DATA
Great course from basics to advanced: https://tinyurl.com/58582b9u
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REST API & MICROSERVICES
Quick & complete course: https://tinyurl.com/3tmvujwm
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VERSION CONTROL (GitHub)
The most comprehensive course, Beginner to Expert:
https://tinyurl.com/mrxtyb57
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MACHINE LEARNING DEPLOYMENT INTO PRODUCTION ENVIRONMENT
Course 1 (Intro in ML in prod): https://imp.i384100.net/MLProduction1
Course 2 (ML&Data Lifecycle in prod): https://imp.i384100.net/MLProduction2
Course 3 (ML Modeling Pipelines in prod): https://imp.i384100.net/MLProduction3
Course 4 (Deploying ML in prod): https://imp.i384100.net/MLProduction4
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DOCKER & KUBERNETES (very important subject and best course on the internet)
The most comprehensive course: https://tinyurl.com/25zjfe24
#DataScienceTutorial #DataScienceCourse #DataAnalysis #DataScienceForBeginners