I literally spent 40 hours finding the perfect roadmap for beginners with a step-by-step weekly guide.
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, e.g., Titanic prediction
Week 3-4 Deep Learning(TensorFlow/PyTorch)
- PyTorch and TensorFlow basics
- CNNs, RNN's and transformers basis
- Make a Sentiment analysis project
Week 5-6 LLMs and Prompt Engineering
- Learn how LLMs work
- Learn how to use OpenAI and Gemini models
- Study RAGs and fine-tuning
- Read LangChain's docs
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 an AI resume screener
Week 9-10 Build your AI portfolio
- Create a minimum of three portfolio projects using GenAI, ML models and DL models
- Polish your GitHub and improve the READMEs
- Connect with AI professionals
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 cold DM's possible
- Finally, launch your own SaaS tool
Outcomes after 90 Days of grinding
- 3 to 5 solid projects on your resume
- Working knowledge of AI/ML
- Ready to freelance, job hunt or launch your own products
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
Reach out us https://byteoniclabs.com if you need any help.
Top comments (0)