IBM AI Engineering Professional Certificate | Coursera [Update 11/2024]
English | Size: 1.69 GB
Genre: eLearning[/center]
Get job-ready as an AI engineer . Build the AI engineering skills and practical experience you need to catch the eye of an employer in less than 4 months. Power up your resume!
What you'll learn
Describe machine learning, deep learning, neural networks, and ML algorithms like classification, regression, clustering, and dimensional reduction
Implement supervised and unsupervised machine learning models using SciPy and ScikitLearn
Deploy machine learning algorithms and pipelines on Apache Spark
Build deep learning models and neural networks using Keras, PyTorch, and TensorFlow
Professional Certificate - 13 course series
AI is expected to grow 36.6% by 2030 (Forbes). This IBM AI Engineering Professional Certificate is ideal for data scientists, machine learning engineers, software engineers, and other technical specialists looking to get job-ready as an AI engineer.
During this program, you'll learn to build, train, and deploy different types of deep architectures, including convolutional neural networks, recurrent networks, autoencoders,and generative AI models including large language models (LLMs).
You'll master fundamental concepts of machine learning and deep learning, including supervised and unsupervised learning, using Python. You'll apply popular libraries such as SciPy, ScikitLearn, Keras, PyTorch, and TensorFlow to industry problems using object recognition, computer vision, image and video processing, text analytics, natural language processing (NLP), and recommender systems. Build Generative AI applications using LLMs and RAG with frameworks like Hugging Face and LangChain.
You'll work on labs and projects that will give you practical working knowledge of deep learning frameworks.
If you're looking to build job-ready skills and practical experience employers are looking for, ENROLL TODAY and build a resume and portfolio that stand out!
Applied Learning Project
Hands-on, Practical Project Work to Showcase Your Skills to Employers
The best way to convince employers you're the right person for the job is to highlight your relevant hands-on experience in an interview.
This PC is specifically designed to help you build the practical experience employers look for. Throughout the program, you'll apply your skills in hands-on labs and projects that fine-tune your new competencies. You'll:
Build deep learning models and neural networks using Keras, PyTorch, and TensorFlow.
Implement supervised and unsupervised machine learning models using SciPy and ScikitLearn, positional encoding, masking, attention mechanism, and document classification.
Create LLMs like GPT and BERT.
Develop transfer learning applications in NLP using major language model frameworks like LangChain, Hugging Face, & PyTorch.
Set up a Gradio interface for model interaction and construct a QA bot using LangChain and LLM to answer questions from loaded documents.
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