Week 1-2 Python + ML concepts -Focus on Numpy, Pandas, OOP, decorators, generators -Watch Andrew Ng's ML course on Coursera -Make a Simple classification or regression project ex-Titanic prediction (2/n)

Week 3-4 Deep Learning(TensorFlow/PyTorch) -PyTorch and TensorFlow basics -CNN's,RNN's and transformers basis -Make a Sentiment analysis project (3/n)

Week 5-6 LLM's and Prompt Engineering -Learn how LLM's work -Learn how to use OpenAI and Gemini models -Study RAG's and fine tuning -Read LangChain's docs (4/n)

Week 7-8 Production AI -Learn how to deploy models using Docker and Github Actions -Learn about MLOp's concepts -Do a basic project like AI resume screener (5/n)

Week 9-10 Build your AI portfolio -Create minimum three portfolio projects using GenAI, ML models and DL models -Polish your Github and improve readme's -Connect with AI professionals (6/n)

Week 11-12 Internship and Job Hunting -Apply to AI engineering and freelance gigs at Upwork or any other platform -Approach newly funded startups and YC companies -Do as many as cold DM's -Finally launch your own SaaS tool (7/n)

Outcomes after 90 Days of grinding -3 to 5 solid projects on your resume -Working knowledge of AI/ML -Ready to freelance and Job hunt or launch your own products (8/n)

How to make it highly paid -Focus on ML and GenAI tools -Offer solutions to big tech companies -Use AI tools to learn more about AI/ML (n/n)

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@sharpeye_wnl

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