Ementorhub

What you'll learn

Job-ready skills employers are crying out for in gen AI, machine learning, deep learning, NLP apps, and large language models in just 6 months.

Build and deploy generative AI applications, agents and chatbots using Python libraries like Flask, SciPy and ScikitLearn, Keras, and PyTorch.

Key gen AI architectures and NLP models, and how to apply techniques like prompt engineering, model training, and fine-tuning.

Apply transformers like BERT and LLMs like GPT for NLP tasks, with frameworks like RAG and LangChain.

Professional Certificate - 16 course series

Building AI agents and applications with RAG and LangChain in a significant guided project.

After completing this course, learners will be able to: • Describe what a neural network is, what a deep learning model is, and the difference between them. • Demonstrate an understanding of unsupervised deep learning models such as autoencoders and restricted Boltzmann machines. • Demonstrate an understanding of supervised deep learning models such as convolutional neural networks and recurrent networks. • Build deep learning models and networks using the Keras library.

Generative AI: Introduction and Applications

Generative AI: Prompt Engineering Basics

Python for Data Science, AI & Development

Developing AI Applications with Python and Flask

Building Generative AI-Powered Applications with Python

Data Analysis with Python

Machine Learning with Python

Introduction to Deep Learning & Neural Networks with Keras

Generative AI and LLMs: Architecture and Data Preparation

Gen AI Foundational Models for NLP & Language Understanding

Generative AI Language Modeling with Transformers

Generative AI Engineering and Fine-Tuning Transformers

Generative AI Advance Fine-Tuning for LLMs

Fundamentals of AI Agents Using RAG and LangChain

Project: Generative AI Applications with RAG and LangChain