Learn Data Science in 180 days๐ค๐ and start your data science career.
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A thread๐งต๐
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A thread๐งต๐
First Month ๐๏ธ
Day 1 to 15 - Learn Python for Data Science
Day 16 to 30 - Learn Statistics for Data Science
Day 1 to 15 - Learn Python for Data Science
Day 16 to 30 - Learn Statistics for Data Science
Second Month ๐๏ธ
Day 31 to 45 - Explore Python Packages( Numpy, Pandas, Matplotlib, Seaborn, Scikit-Learn)
Day 16 to 30 - Implement EDA on real-world datasets.
Day 31 to 45 - Explore Python Packages( Numpy, Pandas, Matplotlib, Seaborn, Scikit-Learn)
Day 16 to 30 - Implement EDA on real-world datasets.
Third Month ๐๏ธ
Day 61 to 75 - Focus on Machine Learning Algorithms
Day 76 to 90 - Implement Ml prediction algorithms on real-world datasets
Day 61 to 75 - Focus on Machine Learning Algorithms
Day 76 to 90 - Implement Ml prediction algorithms on real-world datasets
Fourth Month ๐๏ธ
Day 91 to 105 - Focused on Unsupervised ML Algorithms
Day 106 to 120 - Learn Apriori algorithms, recommendation system, anomaly detection
Day 91 to 105 - Focused on Unsupervised ML Algorithms
Day 106 to 120 - Learn Apriori algorithms, recommendation system, anomaly detection
Fifth Month ๐๏ธ
Day 121 to 135 - Ensemble learning, stacking, optimization techniques, model deployment
Day 136 to 150 - Implement a deployable ML algorithm on real-world problems and datasets
Day 121 to 135 - Ensemble learning, stacking, optimization techniques, model deployment
Day 136 to 150 - Implement a deployable ML algorithm on real-world problems and datasets
Sixth Month ๐๏ธ
Day 151 to 180 - Build Github Profile
- Build a strong portfolio
- Write well-researched articles
Day 151 to 180 - Build Github Profile
- Build a strong portfolio
- Write well-researched articles
โข โข โข
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