ISACA is equipping IT professionals with the latest skills in machine learning (ML) and deep learning (DL) technologies as industries rapidly integrate AI. Building on its introductory “AI Fundamentals” course, ISACA has two new courses to take you beyond just theory and into practical business uses of these powerful AI techniques.
The first new course, “Machine Learning for Business Enablement,” will provide you with a solid grounding in the domains and lifecycle of ML projects. Upon completing this course, you will know how to identify appropriate use cases for ML, weigh the pros and cons of different ML algorithms, and make smart decisions about deploying ML at your enterprise. The course’s structure covers the three main ML approaches – reinforcement, unsupervised, and supervised learning – so you understand the unique strengths of each one. Core ML fundamentals such as data preprocessing, model training and model performance evaluation are also covered in-depth.
Most importantly, you will apply all this new knowledge by engaging in hands-on labs and real-world case studies. The lab activities will allow you to use ML techniques to optimize recommendation systems, do customer segmentation, predict costs and analyze sentiment. Short quizzes throughout the course will help you reinforce your understanding of the key concepts covered.
When you have succeeded in completing “Machine Learning for Business Applications,” you will be ready to expand your knowledge of ML even more by taking “Machine Learning: Neural Networks, Deep Learning, and Large Language Models,” a course covering the specifics of more advanced AI technologies.
You will start by learning about neural network architectures and how they can be specialized for different data types and tasks, like transforming raw image and text inputs into numerical data, or vectors, which can be processed by machines. The core components of neural networks, such as hidden layers, activation functions, and backpropagation, are covered extensively, too. You will examine specialized network architectures like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), and learn about innovations that are driving recent advances in large language models (LLMs) and generative artificial intelligence (Gen AI), including transformer models and attention mechanisms.
Given the importance of responsible AI deployment, the course also covers important and timely topics like prompt engineering and dealing with model issues like hallucinations. You will not only learn how to leverage these powerful AI tools, but you will also learn how to use them responsibly and effectively.
By the end of the course, you will be able to explain how different AI systems work, assess their strengths and limitations, and promote their use to address a wide range of enterprise use cases.
ML pioneer Pedro Domingos said, “Machine learning will not single-handedly determine the future, any more than any other technology; it's what we decide to do with it that counts, and now you have the tools to decide.” (Domingos, P., The Master Algorithm, 2015). As always, ISACA’s latest course offerings are intended to provide you with the tools you need to succeed, too. Whether you are looking to enhance existing systems, try out innovative solutions, or attempt to gain a deeper understanding of transformative AI technologies, ISACA’s “Machine Learning for Business Enablement” and “Machine Learning: Neural Networks, Deep Learning, and Large Language Models” will meet your needs.
