Data science Roadmap

6-Month Roadmap to Becoming a Machine Learning Engineer for Free 19 free lessons to get you interview-ready and move ahead of 90% of people. Follow these steps in the specified order to ensure success: 𝗠𝗼𝗻𝘁𝗵 𝟭: 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝘀 & 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀 Weeks 1-2: Study Linear Algebra concepts - https://lnkd.in/eabKGp_p Weeks 3-4: Continue with Calculus and Probability & Statistics. Practice problems to solidify your understanding - https://lnkd.in/ea2DmZ2d 𝗠𝗼𝗻𝘁𝗵 𝟮: 𝗦𝗤𝗟 & 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 𝗮𝗻𝗱 𝗠𝗼𝗿𝗲 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀 Weeks 1-2: Learn SQL basics - https://lnkd.in/ea2DmZ2d Weeks 3-4: Continue studying Probability & Statistics. Apply statistical concepts in SQL where possible. 𝗠𝗼𝗻𝘁𝗵 𝟯: 𝗖𝗼𝗿𝗲 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝗼𝗳 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 Weeks 1-2: Go through Google's ML Crash Course - https://lnkd.in/eT7NiGp6 Weeks 3-4: Go through Andrew Ng's ML Course - https://lnkd.in/e964AiC7 𝗠𝗼𝗻𝘁𝗵 𝟰: 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗦𝗸𝗶𝗹𝗹𝘀 (𝗣𝘆𝘁𝗵𝗼𝗻 & 𝗟𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀) Weeks 1-2: Learn Python basics. https://lnkd.in/euyfHHxa Weeks 3-4: Start with Python libraries for Machine Learning. • Scikit-learn - https://lnkd.in/eqFhCwXt • TensorFlow - https://lnkd.in/e6RWbe9h • PyTorch - https://lnkd.in/efhPxZPM 𝗠𝗼𝗻𝘁𝗵 𝟱: 𝗠𝗼𝗱𝗲𝗹 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 & 𝗧𝘂𝗻𝗶𝗻𝗴 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀, 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹𝘀 Weeks 1-2: Learn about model training and tuning techniques. • Intermediate ML - https://lnkd.in/e89AmkzE • Hyperparameter Tuning - https://lnkd.in/ezEnqeG2    Weeks 3-4: Start with Advanced Deep Learning Models. • Stanford's CS231n (CNNs) - http://cs231n.github.io/ • Deep Learning Book - https://lnkd.in/e_utEgZM 𝗠𝗼𝗻𝘁𝗵 𝟲: 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁, 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴, & 𝗠𝗮𝗶𝗻𝘁𝗲𝗻𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝗥𝗲𝘀𝘂𝗺𝗲 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻, 𝗦𝗼𝗳𝘁 𝗦𝗸𝗶𝗹𝗹𝘀 & 𝗧𝗶𝗽𝘀 Weeks 1-2: Learn about deployment, monitoring, and maintenance. • Docker - https://lnkd.in/esXHzx9k • Git - https://lnkd.in/esQ8FMxS • AWS ML - https://lnkd.in/eZcdQPee • Azure ML - https://lnkd.in/e5fvmvtk    Weeks 3-4: Prepare your resume and improve your soft skills Resume and Soft Skills & Tips, and work on projects. • 217 Machine Learning Projects - https://lnkd.in/e5kyv3Tv

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6-Month Roadmap to Becoming a Machine Learning Engineer for Free 19 free lessons to get you interview-ready and move ahead of 90% of people. Follow these steps in the specified order to ensure success: 𝗠𝗼𝗻𝘁𝗵 𝟭: 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝘀 & 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀 Weeks 1-2: Study Linear Algebra concepts - https://lnkd.in/eabKGp_p Weeks 3-4: Continue with Calculus and Probability & Statistics. Practice problems to solidify your understanding - https://lnkd.in/ea2DmZ2d 𝗠𝗼𝗻𝘁𝗵 𝟮: 𝗦𝗤𝗟 & 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲𝘀 𝗮𝗻𝗱 𝗠𝗼𝗿𝗲 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀 Weeks 1-2: Learn SQL basics - https://lnkd.in/ea2DmZ2d Weeks 3-4: Continue studying Probability & Statistics. Apply statistical concepts in SQL where possible. 𝗠𝗼𝗻𝘁𝗵 𝟯: 𝗖𝗼𝗿𝗲 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝗼𝗳 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 Weeks 1-2: Go through Google's ML Crash Course - https://lnkd.in/eT7NiGp6 Weeks 3-4: Go through Andrew Ng's ML Course - https://lnkd.in/e964AiC7 𝗠𝗼𝗻𝘁𝗵 𝟰: 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗦𝗸𝗶𝗹𝗹𝘀 (𝗣𝘆𝘁𝗵𝗼𝗻 & 𝗟𝗶𝗯𝗿𝗮𝗿𝗶𝗲𝘀) Weeks 1-2: Learn Python basics. https://lnkd.in/euyfHHxa Weeks 3-4: Start with Python libraries for Machine Learning. • Scikit-learn - https://lnkd.in/eqFhCwXt • TensorFlow - https://lnkd.in/e6RWbe9h • PyTorch - https://lnkd.in/efhPxZPM 𝗠𝗼𝗻𝘁𝗵 𝟱: 𝗠𝗼𝗱𝗲𝗹 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 & 𝗧𝘂𝗻𝗶𝗻𝗴 𝗧𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀, 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹𝘀 Weeks 1-2: Learn about model training and tuning techniques. • Intermediate ML - https://lnkd.in/e89AmkzE • Hyperparameter Tuning - https://lnkd.in/ezEnqeG2    Weeks 3-4: Start with Advanced Deep Learning Models. • Stanford's CS231n (CNNs) - http://cs231n.github.io/ • Deep Learning Book - https://lnkd.in/e_utEgZM 𝗠𝗼𝗻𝘁𝗵 𝟲: 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁, 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴, & 𝗠𝗮𝗶𝗻𝘁𝗲𝗻𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝗥𝗲𝘀𝘂𝗺𝗲 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻, 𝗦𝗼𝗳𝘁 𝗦𝗸𝗶𝗹𝗹𝘀 & 𝗧𝗶𝗽𝘀 Weeks 1-2: Learn about deployment, monitoring, and maintenance. • Docker - https://lnkd.in/esXHzx9k • Git - https://lnkd.in/esQ8FMxS • AWS ML - https://lnkd.in/eZcdQPee • Azure ML - https://lnkd.in/e5fvmvtk    Weeks 3-4: Prepare your resume and improve your soft skills Resume and Soft Skills & Tips, and work on projects. • 217 Machine Learning Projects - https://lnkd.in/e5kyv3Tv

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