IBM Generative AI Engineering Professional Certificate
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Program
IBM Generative AI Engineering Professional Certificate
Master the skills to build and deploy generative AI applications using tools like LangChain and PyTorch, and get job-ready—no prior AI experience required.
Self-Paced
Mentored
Intermediate
Duration
6 months
Artificial intelligence is experiencing rapid growth, with industry projections estimating a 36.6% increase by 2030 (Forbes). The Generative AI Engineering Professional Certificate is designed for technical professionals such as data scientists, machine learning engineers, and software developers who are looking to gain the expertise needed to transition into AI-focused roles. This program offers a practical, hands-on approach to learning, helping you build job-ready skills in a fast-evolving tech landscape.
Throughout the program, you'll learn how to design, train, and deploy deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), autoencoders, and generative AI systems like large language models (LLMs). You'll explore key concepts in machine learning and deep learning—such as supervised and unsupervised learning—using Python. The program integrates powerful libraries and frameworks like TensorFlow, Keras, PyTorch, SciPy, and Scikit-learn to solve real-world problems in image processing, natural language understanding, computer vision, and recommendation systems.
You’ll also get hands-on experience in developing generative AI applications using advanced techniques like retrieval-augmented generation (RAG) and tools such as Hugging Face and LangChain. With guided labs and real-world projects, you’ll gain the practical experience needed to apply these skills in professional settings. By the end of the program, you’ll have a portfolio of work that highlights your capabilities and makes you stand out to potential employers in the AI space.
This Certificate Program comprises 16 purposely designed courses that take you on a carefully defined tangible learning path.
It is a self-paced program, which means it isn’t run to a fixed schedule with regard to completing courses or submitting assignments. To give you an idea of how long the program takes to complete, it is anticipated that if you work 4-6 hours per week, you will complete the program in 6 months. However, as long as the program is completed before the end date, you can work at your own pace. The materials for each course module will become available when you start the particular course.
You can choose to enroll for the complete Certificate Program in one go, or sign up for individual courses one at a time. Each course that you complete will take you a step closer to acquiring the Professional Certificate. And it’s worth noting that some courses may also qualify for other learning paths.
Overall, for students keen to expand their career options to include AI, this is a superb opportunity to showcase your AI development skills.
- By the end of this program, you will be able to:
- Explain the key concepts of generative AI, machine learning, deep learning, NLP, and large language models.
- Use Python libraries like Flask, Scikit-learn, Keras, and PyTorch to design and deploy GenAI applications, chatbots, and intelligent agents.
- Compare GenAI architectures and NLP models, including transformers like BERT and LLMs like GPT, to understand their strengths and limitations.
- Evaluate advanced AI techniques such as prompt engineering, model training, and fine-tuning to improve model performance.
- Build and deploy a complete generative AI application using LLMs, RAG, and LangChain to solve real-world NLP problems.
- Identify the ethical risks and biases in GenAI technologies and propose responsible AI development strategies.
- Software developers, data scientists, and ML engineers
- AI enthusiasts wanting to specialize in generative AI
- Professionals with basic Python knowledge
- Those seeking hands-on experience with LLMs, NLP, and AI apps
- Early-career tech professionals aiming to enter AI engineering
- Basic computer literacy
- Working knowledge of Python
Program Outline
Master AI fundamentals, from machine learning and neural networks to generative AI and LLMs. Explore real-world applications in NLP, computer vision, and robotics, and gain hands-on skills for a career in AI.
Topic Covered:
Introduction and Applications of AI
AI Concepts, Terminology, and Application Domains
Business and Career Transformation Through AI
Issues, Concerns, and Ethical Considerations
You can choose to enroll for this individual course. Click here to see course details.
Dive into the new and exciting world of generative AI and large language models (LLM). Understand the capabilities of generative AI and its use cases in the real world. Identify the applications of generative AI in different sectors and industries.
Topic Covered:
Introduction and Capabilities of Generative AI
Applications and Tools of Generative AI
Course Quiz and Final Project
You can choose to enroll for this individual course. Click here to see course details.
Master the art of prompting. Learn proven techniques to craft effective prompts that unlock the full potential of any LLM.
Topic Covered:
Prompt Engineering for Generative AI
Prompt Engineering: Techniques and Approaches
Text-to-Image Prompts and IBM watsonx
You can choose to enroll for this individual course. Click here to see course details.
This Python course provides a beginner-friendly introduction to Python for data science. Practice through lab exercises, and you'll be all set to create your first Python script!
Topic Covered:
Python Basics
Python Data Structures
Python Programming Fundamentals
Working with Data in Python
APIs and Data Collection
You can choose to enroll for this individual course. Click here to see course details.
Master AI-enabled application development with Python and Flask while working on real projects. Strengthen your portfolio with a fully functional AI-powered web app.
Topic Covered:
Python Coding Practices and Packaging Concepts
Web App Deployment using Flask section
Creating AI Application and Deploy using Flask section
You can choose to enroll for this individual course. Click here to see course details.
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.
Topic Covered:
Image Captioning with Generative AI
Create Your Own ChatGPT-Like Website
Create a Voice Assistant
Generative AI-Powered Meeting Assistant
Summarize Your Private Data with Generative AI and RAG
Babel Fish (Universal Language Translator) with LLM and STT TTS
You can choose to enroll for this individual course. Click here to see course details.
Get started with Python and build essential skills for data analysis in just 5 weeksno prior programming experience is required.
Topic Covered:
Importing Data sets
Data Wrangling
Exploratory Data Analysis
Model Development
Model Evaluation
You can choose to enroll for this individual course. Click here to see course details.
Unlock hidden insights and predict future trends with the power of machine learning! Dive into both supervised and unsupervised learning, and set yourself you up for success in the world of data-driven predictions.
Topic Covered:
Introduction to Machine Learning
Regression
Classification
Clustering
Recommender Systems
You can choose to enroll for this individual course. Click here to see course details.
Master the fundamentals of deep learning with IBM! Explore neural networks, supervised & unsupervised models. Learn how to build, train, and test deep learning models using Keras.
Topic Covered:
Introduction to Deep Learning and Neural Networks
Basics of Deep Learning
Keras and Deep Learning Libraries
Deep Learning Models
You can choose to enroll for this individual course. Click here to see course details.
Build in-demand, job-ready generative AI architecture and data science skills in less than a month. No programming experience is required.
Topic Covered:
Generative AI Architecture
Data Preparation for LLMs
You can choose to enroll for this individual course. Click here to see course details.
Build job-ready AI models using NLP and earn valuable practical experience and credentials in just three weeks.
Topic Covered:
Fundamentals of Language Understanding
Word2Vec and Sequence-to-Sequence Models
You can choose to enroll for this individual course. Click here to see course details.
Build job-ready skills for language modeling in just 3 weeks. Plus, valuable practical experience and a credential.
Topic Covered:
Fundamental Concepts of Transformer Architecture
Advanced Concepts of Transformer Architecture
You can choose to enroll for this individual course. Click here to see course details.
Advance your AI career with practical skills in fine-tuning transformers and Gen AI models. Get hands-on with Hugging Face, PyTorch, LoRA, and QLoRA to stand out in interviews.
Topic Covered:
Transformers and Fine-Tuning
Parameter Efficient Fine-Tuning (PEFT)
You can choose to enroll for this individual course. Click here to see course details.
Master the art of fine-tuning LLMs to boost accuracy, align with business goals, and unlock actionable insights that drive innovation.
Topic Covered:
Different Approaches to Fine-Tuning
Fine-Tuning Causal LLMs with Human Feedback and Direct Preference
You can choose to enroll for this individual course. Click here to see course details.
Gain job-ready skills in building AI agents in just 2 weeks. Build valuable practical experience and an industry-recognized credential. Build familiarity with RAG and LangChain.
Topic Covered:
RAG Framework
Prompt Engineering and LangChain section
You can choose to enroll for this individual course. Click here to see course details.
Build a real-world generative AI app using LangChain, RAG, and vector databases. Gain hands-on skills to boost your AI career and impress in interviews.
Topic Covered:
Document Loader Using LangChain
RAG Using LangChain
Create a QA Bot to Read Your Document
You can choose to enroll for this individual course. Click here to see course details.
Why Learn with SkillUp Online?
We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.
Reskilling into tech? We’ll support you.
Upskilling for promotion? We’ll help you.
Cross-skilling for your career? We’ll guide you.
Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
Designed by the industry for the industry so you can build job-ready skills.
Job-Ready Skills Focus
Competency building and global certifications employers are actively looking for.
FAQs
The IBM Generative AI Engineering Professional Certificate is a comprehensive GenAI engineering program designed to help learners build the technical foundation needed for generative AI for engineering roles. It covers Python, AI model development, prompt engineering for LLMs, and deployment of AI applications using Flask and LangChain.
Yes. This professional certificate in generative AI offers industry-relevant training, hands-on projects, and guided labs that help you gain job-ready skills in AI and ML. You’ll master tools like Hugging Face transformers and RAG to build and deploy real-world AI applications, making it one of the best generative AI programs available online.
If you’re looking for the best generative AI certificate course/program, this IBM generative AI engineer program stands out for its balance of foundational AI learning and advanced LLM training. Learners gain end-to-end exposure—from AI fundamentals and Python programming to transformers, RAG, and fine-tuning GenAI models.
Learners typically complete the IBM Generative AI Engineering Professional Certificate in 5–6 months with consistent study. The self-paced and instructor-led courses allow flexible learning while ensuring a structured progression through Generative AI, ML, and LLM projects.
Completing this generative AI engineer course can open roles such as generative AI engineer, AI developer, machine learning engineer, and LLM application developer. The Generative AI professional certificate prepares you to build AI-powered solutions and contribute to innovative AI-driven systems.
Basic Python knowledge is recommended but not mandatory. The program includes Python fundamentals for beginners and AI applications with Python and Flask to help you learn and apply programming for generative AI for engineering tasks.
Yes. You’ll explore transformers and LLM architectures, including GPT, BERT, and LLaMA, in this program. You not only get theoretical understanding but also hands-on experience with cutting-edge IBM generative AI tools and frameworks.
Through the IBM generative AI program, learners develop AI-powered chatbots, text generators, and RAG-based applications using LangChain and Hugging Face. Projects also include deploying GenAI models with Flask and implementing generative AI with Python in real-world use cases.
Yes. You’ll earn an IBM Certificate, validating your technical expertise and demonstrating your readiness for professional roles in generative AI engineering.
This IBM Generative AI Engineering Professional Certificate blends structured coursework, real projects, and practical tools like RAG, LangChain, and Transformers. It provides generative AI training online that’s directly aligned with career outcomes, unlike many theory-only programs.
Absolutely. The program starts with foundational AI and Python courses before progressing into advanced topics like fine-tuning and LLMs. Whether you’re a beginner or a professional upskilling in AI, this generative AI engineer program offers a guided path to success.
Program Offering
Type of certificate
IBM Professional Certificate
About this program
16 Courses
73 Skills
Includes
Discussion Space
127 Hands-on labs
50 Practice quizzes
49 Graded quizzes
04 Final exams
08 Final projects
Create
Use Generative AI for text, images, and educational content
Build and deploy web apps and APIs (Flask, chatbots, assistants)
Perform data analysis and develop ML models (Keras, recommendation systems)
Build and train language models (N-gram, Seq2Seq, Transformers, BERT)
Fine-tune models with PyTorch, Hugging Face, and reinforcement learning (PPO, DPO)
Summarize and query private documents using RAG, LangChain, and QA bots
Store and retrieve data using vector databases and web scraping
Exercises to explore
AI assistant-user interactions and business use cases with generative AI
Text, image, and code generation using generative AI tools
Prompt engineering techniques
Using Watsonx Prompt Lab
Python programming fundamentals, file handling, and IDE usage
Web app development and chatbot integration using Flask
Data import, wrangling, and analysis with Pandas
Building and evaluating ML models
Deep learning concepts
Fine-tuning LLMs, applying RAG, LangChain, and building interfaces
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