Artificial intelligence: Real-world Applications
Advanced analytics such as artificial intelligence and machine learning are becoming increasingly critical to developing innovative, differentiated, competitive, and successful businesses and products. AI in particular has the potential to unlock the value of data, and ultimately transform businesses and entire industries, not to mention improve and enhance human experiences.
Join expert Alex Castrounis for a high-level overview of real-world artificial intelligence and machine learning applications. You'll explore different applications of AI and machine learning, including prediction, recommender systems, recognition (images, audio, text), computer vision, clustering, anomaly detection, and natural language, and learn how to leverage them to solve real-world problems and create value from data.
What you'll learn-and how you can apply it
By the end of this live, online course, you’ll understand:
- Different types of real-world AI and machine learning applications and examples, including prediction, recommender systems, recognition (images, audio, text), computer vision, clustering, anomaly detection, and natural language
- Ways AI and machine learning can be leveraged to solve real-world problems and create value from data, achieve business goals, and improve human experiences
- How to use this information to help develop an AI strategy
This training course is for you because...
- You're a business executive or technical practitioner interested in learning more about artificial intelligence.
- No technical expertise required
About your instructor
Alex is the author of AI for People and Business, a data science and advanced analytics innovation consultant, and the founder of InnoArchiTech. He has an M.S. in applied mathematics, awarded with distinction, and nearly 20 years of innovation experience. Alex has helped companies in many industries turn data into value and competitive advantage, build great products and teams, and ultimately to win!
The timeframes are only estimates and may vary according to how the class is progressing
This course is taught continuously for an hour and will consist of the topics listed below. Questions will be answered throughout the course, where possible, and time frame will be allotted at the end for Q&A.
- Recommender systems
- Recognition (images, audio, text)
- Computer vision
- Clustering and anomaly detection
- Natural language processing, generation, and understanding
- Hybrid and miscellaneous