- Developed a Fully autonomous intelligent travel agent that can understand userpreferences and search for flights, hotels, attractions and can take action andbook for the user.- Designed the basic pipeline flow of the travel agent.- Took advantage of in-context-learning to get the expected output from LLM.- Fine-tuned Llama-v2-chat using parameter efficient tuning or PEFT.- Used LangChain to give the LLM memory and to decide which actions to use.

• Helped 50+ students to finish this specialization by clarifying certain concepts.•Took the initiative of starting a series of learning posts, that helped more than1000 students. These posts weren't in the course's scope. Inspiring fellowmentors to also post about new topics.• Reviewed more than 200 Student's Questions, and help them fix bugs in theirassignments.• Guided them for their machine learning career