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IBM

Generative AI Engineering

IBM via edX Professional Certificate

Overview

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The gen AI market is projected to grow at an impressive 46% CAGR through 2030 (Statista). The demand for tech professionals skilled in generative AI engineering is skyrocketing! This Generative AI Engineering Professional Certificate gives aspiring generative AI engineers, AI developers, data scientists, machine learning engineers, and AI researchers the critical skills in generative AI, large language models (LLMs), and natural language processing (NLP) that employers are looking for.

By utilizing transformers and LLMs, gen AI engineers create AI systems, applications and agents that generate and process new data—such as images, text, audio, and video.

During this program, you'll explore AI, generative AI, and prompt engineering, as well as data analysis, machine learning, and deep learning with Python. You'll gain hands-on experience with libraries like SciPy and scikit-learn, and develop applications using frameworks and models like BERT, GPT, and LLaMA. You'll also learn how to build LLM-based NLP applications using tools like Hugging Face Transformers, PyTorch, RAG, and LangChain, while diving deep into tokenization, language models, and transformer methods.

The program offers ample practical experience through hands-on labs and projects you can showcase in interviews. Additionally, you’ll complete a substantial guided project where you’ll build your own real-world generative AI application.

If you're eager to set yourself apart with the highly sought-after generative AI skills that employers are actively looking for, ENROLL TODAY and advance your career in less than 6 months! Prerequisites: Just basic computer literacy... No prior experience required.

Syllabus

Courses under this program:
Course 1: AI for Everyone: Master the Basics

Learn what Artificial Intelligence (AI) is by understanding its applications and key concepts including machine learning, deep learning and neural networks.



Course 2: Introduction to Generative AI

In this course, you will learn about the fundamentals of generative AI. You will explore the capabilities and applications of generative AI across different domains. You will explore the capabilities and features of common generative AI models and tools.



Course 3: Introduction to Prompt Engineering

In this course, you will learn about prompt engineering to unlock the full potential of generative AI tools like ChatGPT. You will learn the techniques and best practices for writing effective prompts and explore a few common prompt engineering tools.



Course 4: Python Basics for Data Science

This Python course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you'll be ready to create your first Python scripts on your own!



Course 5: Python for AI & Development Project

This mini-course introduces you to the process for unit testing Python code, including building and running unit tests and packaging the Python application for distribution.



Course 6: Developing Generative AI Applications with Python

Build in-demand skills in generative AI application development and get hands-on experience creating intelligent chatbots and apps using popular LLMs, RAG technology, and IBM watsonx.



Course 7: Analyzing Data with Python

In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn!



Course 8: PyTorch Basics for Machine Learning

This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. You will quickly iterate through different aspects of PyTorch giving you strong foundations and all the prerequisites you need before you build deep learning models.



Course 9: Deep Learning Fundamentals with Keras

New to deep learning? Start with this course, that will not only introduce you to the field of deep learning but give you the opportunity to build your first deep learning model using thepopular Keras library.



Course 10: Mastering Generative AI: LLM Architecture & Data Preparation

Build in-demand, job-ready generative AI architecture and data science skills in two weeks. A basic knowledge of Python and PyTorch and an awareness of machine learning and neural networks would be an advantage, though not strictly required.



Course 11: Mastering Generative AI: Model Foundations and NLP

Gain job-ready skills in generative AI and NLP that employers need. Enhance your resume with in-demand expertise that will help you stand out as an AI engineer, AI developer, or data scientist.



Course 12: Mastering Generative AI: Language Models with Transformers

Build job-ready skills in NLP based applications using GPT and BERT in just 2 weeks! Add sought-after skills employers are looking for to your resume and power up your AI career.



Course 13: Mastering Generative AI: Fine-Tuning Transformers

Gain job-ready AI engineering skills for working with transformers, LLM frameworks, and GPT, and learn how to fine-tune models using Hugging Face and PyTorch.



Course 14: Mastering Generative AI: Advanced Fine-Tuning for LLMs

Build advanced, job-ready skills in fine-tuning using Hugging Face, reinforcement learning using proximal preference optimization (PPO), and optimal solutions for direct preference optimization (DPO).



Course 15: Mastering Generative AI: Agents with RAG and LangChain

Power up your resume with in-demand RAG and LangChain skills employers are looking for. Dive into the world of retrieval augmented generation (RAG), Hugging Face, and LangChain and take your gen AI career up a gear in just 2 weeks!



Course 16: Mastering Generative AI Project: RAG and LangChain App

Get valuable practical experience building a real-world gen AI application that you can talk about in interviews.



Courses

Taught by

Antonio Cangiano, Rav Ahuja, Ramesh Sannareddy, Joseph Santarcangelo and Alex Aklson

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