Artificial Intelligence Practitioner

The Artificial Intelligence (AI) Practitioner track prepares students for careers in AI through the learning of AI concepts, machine and deep learning, deep learning, AI ethics, ML algorithms, and natural language processing (NLP). Explore use cases and applications of AI and demonstrate AI in action with practical labs. Upon successful completion of all course modules, quizzes, and the final exam, students will earn the Artificial Practitioner certification. Along the way, you’ll deep dive into ways that AI makes predictions, understands language and images, and learns using circuits inspired by the human brain. After a hands-on simulation in which you build and test a machine learning model, you’ll finish with tips on how to find your own career in artificial intelligence. Explore essential algorithms, such as linear regression and clustering algorithms; fundamental concepts, techniques, and applications of machine learning; and data preprocessing. You will engage with scenario-based activities and tool-based simulations to apply your learning to real-world scenarios.

What You’ll Learn:

• Introduction to Artificial Intelligence
• Natural Language Processing and Computer Vision
• Machine Learning and Deep Learning
• Describe the fundamental concepts and characteristics of machine learning algorithms
• Analyze the significance of data visualization as a tool for enhancing data exploration processes
• Explain how supervised machine learning models learn from input data to make predictions or decisions
• Explain the role of natural language processing (NLP) in technology across multiple disciplines
• Analyze NLP techniques, algorithms, and tools pertaining to sentiment analysis
• Explain the fundamentals of unsupervised learning
• Define the role of AI in smart cities, smart homes, and smart ecosystems
• Design a plan to solve problems in business using AI
• Determine how to improve the customer experience with AI
• Apply AI techniques for business and supply chain decisions
• Evaluate the types of AI used in supply chain problems
• Explain how AI addresses challenges in risk management in different business sectors
• Determine how AI addresses challenges in human resources

Credentials You’ll Earn:

1. Machine Learning Methods and Tools
2. Data Analytics for Machine Learning
3. Supervised Learning Methods
4. Natural Language Processing
5. Unsupervised Learning Methods
6. AI Applications
7. IBM Artificial Intelligence Practitioner

Time to complete: 70 hours