Last Friday was my last day at megacorp. I am thankful for the four years at my first job as a Software Engineer. Today I have an incredible opportunity to dedicate myself full time in advancing my personal projects and going deep into GenAI while living in SF. Right place, right time.
Though I already have some beginner experience such as building my own home server for working with LLM and Stable Diffusion. I want to refresh my ML foundation and hold myself accountable to a structured plan over the next 8 weeks of runway. So long as I achieve my laid out goals, I can continue building my projects. I have debated what is the best way of getting up to speed with the GenAI community fast. I want to be competent enough to contribute to the massive energy happening right now as I felt going to Ollama‘s meetup last Monday. Formally rebuild my foundation or just learn as I build (honestly leaning to the latter), but I will do both since it seems I already started at the end with high interest areas and now moving backwards to foundations to deepen my understanding.
PS: I am applying for jobs.
I asked ChatGPT to layout an 8 week plan for “how can i learn everything i can learn as a beginner about generative ai and become an expert at it”.
Week 1-2: Fundamentals of AI and Machine Learning
Objective: Understand the basics of AI, machine learning, and neural networks.
• Complete an introductory course on AI and ML (Coursera’s “Machine Learning” by Andrew Ng is highly recommended).
• Read chapters 1-3 of “Deep Learning” by Ian Goodfellow.
Week 3-4: Deep Learning Essentials
Objective: Get familiar with deep learning, focusing on CNNs and RNNs.
•Complete a deep learning course (fast.ai offers a practical, hands-on course).
• https://course.fast.ai/
• https://lnkd.in/ghhSsD9u
• Implement basic projects using TensorFlow or PyTorch (e.g., image classifier with CNN, text generation with RNN).
Week 5-6: Introduction to Generative AI
Objective: Understand and implement simple generative models.
• Study GANs and VAEs through tutorials and implement simple models.
• Explore tutorials on transformers and attempt to fine-tune a pre-trained model for a text generation task.
Week 7: Advanced Generative AI Models
Objective: Dive deeper into advanced generative models and applications.
• Read research papers or summaries on GPT and DALL·E.
• Experiment with more complex projects, such as using GANs for more sophisticated image generation or exploring text-to-image generation models.
Week 8: Real-world Applications and Exploration
Objective: Apply knowledge to a real-world problem or creative project.
• Identify a project that interests you, such as creating a chatbot, generating art, or synthesizing data.
• Begin building your project
Good plan?
Either way I’m excited for this new chapter. It’s been so much fun following the real time advancement and sharing of ideas.
