
Explore the fundamentals of generative AI engineering for beginners through a practical roadmap, covering GitHub for data science, continuous integration for data science, prompt engineering, rag application, and fine tuning.
Create a chatgpt clone with gemini and streamlit
Master version control with git and GitHub by building a repository, cloning, committing changes, and pushing code to the cloud for collaborative data science projects.
Master GitHub basics with repository setup, readme, MIT license, and pushing real code, then explore Lang chain agents and Gemini integration for a data-driven AI demo.
Learn to implement continuous integration for data science with GitHub actions, using feature branches, pull requests, automated tests, and a yaml workflow to run tests.
Convert text into vector representations with word embeddings to capture semantic relationships between words. Learn about word2vec, cbow, skip-gram, and embeddings like Bert, OpenAI, and Gemini for NLP tasks.
Explore Hugging Face as an open source platform for in-house model deployment, fine tuning, and sentiment classification with transformers, tokenizers, and datasets for secure, cost-effective AI.
Discover ai automation by building an llm-driven system that integrates archive research, google news api, and serp api to generate and deliver daily ai updates via newsletter and whatsapp.
Generative AI for Beginners: (Cover Langchain, Prompt Engineering ,Hugging Face, RAG , Fine Tunning to get you started in Generative AI in less than 5 hours).
(Basic's + Demo Use case for all)
Why Take This Course?
Artificial Intelligence is revolutionizing industries across the globe, creating unprecedented opportunities for innovation and growth. By diving into Generative AI, you're positioning yourself at the forefront of this technological revolution. Here's why this course is crucial for your career:
1. High Demand: AI engineers are among the most sought-after professionals in tech, with demand far outpacing supply.
2.Lucrative Career: Generative AI offers some of the highest salaries in the tech industry, reflecting the value and scarcity of these skills.
3. Innovation Driver: Gain the skills to create cutting-edge AI solutions that can solve real-world problems and transform industries.
4. Future-Proof Skills: AI is here to stay. These skills will remain relevant and valuable for decades to come.
5. Versatility: The knowledge gained is applicable across various sectors, from healthcare to finance, retail to robotics.
This course provides a comprehensive introduction to Generative AI, equipping you with practical, in-demand skills that will set you apart in the job market and open doors to exciting career opportunities.
Course Content
In this Generative AI for Beginners course, you will learn:
1. GitHub for Data Science: Version control and collaboration tools for managing data science projects.
2. CI for Data Science: Continuous Integration practices tailored for data science workflows.
3. Prompt Engineering: Techniques to effectively communicate with and guide AI models.
4. RAG (Retrieval-Augmented Generation): Methods to enhance AI responses with external knowledge.
5. Fine-tuning: Customizing pre-trained AI models for specific tasks or domains.
6. AI Automation: Streamlining AI processes and workflows for increased efficiency.
7. Hugging Face: Utilizing this popular platform for accessing and deploying AI models.
This is a short course with a perfect blend of theory + code.
One can take this course understanding everything and then choose the use case they want and dive deep.