IBM AI Engineering Professional Certificate

Become an AI Engineer: Master In-Demand Skills

The field of AI is exploding, with Forbes predicting 36.6% growth by 2030. This IBM AI Engineering Professional Certificate is your gateway to becoming a job-ready AI engineer, perfect for data scientists, machine learning engineers, software engineers, and other technical specialists.

In this program, you’ll gain the expertise to build, train, and deploy various deep learning architectures, including convolutional neural networks, recurrent networks, autoencoders, and cutting-edge Generative AI models like large language models (LLMs).

You’ll master the core concepts of machine learning and deep learning, including supervised and unsupervised learning, all while using Python. You’ll apply popular libraries such as SciPy, Scikit-learn, Keras, PyTorch, and TensorFlow to solve real-world industry problems in areas like:

• Object recognition and computer vision
• Image and video processing
• Text analytics and natural language processing (NLP)
• Recommender systems
• Building Generative AI applications with LLMs and RAG (Retrieval Augmented Generation) using frameworks like Hugging Face and LangChain.

Hands-On Learning: Build a Standout Portfolio

This certificate is designed for practical application. You’ll complete numerous labs and projects, giving you hands-on experience with deep learning frameworks. This practical project work is key to building a resume and portfolio that catches employers’ attention.

Throughout the program, you’ll apply your new skills to:

• Build deep learning models and neural networks using Keras, PyTorch, and TensorFlow.
• Implement supervised and unsupervised machine learning models using SciPy and Scikit-learn, incorporating advanced techniques like positional encoding, masking, attention mechanisms, and document classification.
• Create LLMs, including those similar to GPT and BERT.
• Develop transfer learning applications in NLP using major language model frameworks like LangChain, Hugging Face, and PyTorch.
• Set up a Gradio interface for model interaction and construct a QA bot using LangChain and an LLM to answer questions from loaded documents.

Ready to build job-ready skills and the practical experience employers are looking for? Enroll today and start building a resume and portfolio that stands out!