Artificial Intelligence with Machine Learning
Course number: CGIAIML40
This course covers the crucial skills you need for a successful career in artificial intelligence (AI). You will master the concepts of the machine and deep learning – plus the programming languages needed to excel in an AI career with exclusive training and certification. You will learn how to design intelligent models and advanced artificial neural networks; and leverage predictive analytics to solve real-time problems in this course.
What will you learn?
- Learn about the major applications of Artificial Intelligence across various use cases across various fields like customer service, financial services, and healthcare.
- Implement classical Artificial Intelligence techniques such as search algorithms, neural networks, and tracking
- Gain the ability to apply Artificial Intelligence techniques for problem-solving and explain the limitations of current Artificial Intelligence techniques
- Master the skills and tools used by the most innovative Artificial Intelligence teams across the globe as you delve into specializations, and gain experience solving real- world challenges
- Design and build your own intelligent agents and apply them to create practical Artificial Intelligence projects including games, Machine Learning models, logic constraint satisfaction problems, knowledge-based systems, probabilistic models, agent decision-making functions, and more
- Understand the concepts of TensorFlow and its main functions, operations, and the execution pipeline
- Understand and master the concepts and principles of Machine Learning, including its mathematical and heuristic
- Master and comprehend advanced topics such as convolutional neural networks, recurrent neural networks, training deep networks, and high- level interfaces
- Learn to deploy deep learning models on Docker, Kubernetes, and in serverless environments (cloud)
- Understand the fundamentals of Natural Language Processing using the most popular library; Python’s Natural Language Toolkit (NLTK)
Target Audience
With the demand for Artificial Intelligence in a broad range of industries such as banking and finance, manufacturing, transport and logistics, healthcare, home maintenance, and customer service, the Artificial Intelligence course is well suited for a variety of profiles such as:
- Developers aspiring to be Artificial Intelligence engineers or Machine Learning engineers
- Analytics managers who are leading a team of analysts
- Information architects who want to gain expertise in Artificial Intelligence algorithms
- Graduates looking to build a career in Artificial Intelligence and Machine Learning
Certification
AI Certification by IBM
Exam
AI Exam from IBM
Accreditation
Post class completion, students can appear for the AI exam from IBM.
Course Content
This course is designed to help learners decode the mystery of Artificial Intelligence and understand its business applications. The course provides an overview of Artificial Intelligence concepts and workflows, Machine Learning, Deep Learning, and performance metrics. You will learn the difference between supervised and unsupervised learning, be exposed to use cases, and see how clustering and classification algorithms help identify Artificial Intelligence business applications.
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This course will make you an expert in Machine Learning, a form of Artificial Intelligence that automates data analysis to enable computers to learn and adapt through experience to do specific tasks without explicit programming. You will master Machine Learning concepts and techniques, including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms and prepare you for your role with advanced Machine Learning knowledge.
This course will refine your machine learning knowledge and make you an expert in Deep Learning using TensorFlow. Master the concepts of deep learning and TensorFlow to build artificial neural networks and traverse layers of data abstraction. This course will help you to unlock the power of data and prepare you for new horizons in AI.
This course covers real applications of computer vision, generative-adversarial networks (GANs), distributed and parallel computing with GPUs, and deployment of deep learning models on cloud.
This project will allow you to implement the skills that you learned in the program. With dedicated mentoring sessions, you will learn how to solve a real industry-aligned problem. You will learn various Artificial Intelligence-based supervised and unsupervised techniques such as Regression, SVM, Tree-based algorithms, and NLP.
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