CEO BigDataTrunk&Certify360.ai | Author

This is live session we do for Stanford but have opportunity to include public audience.
Differentiate AI, Machine Learning, and Deep Learning with confidence.
Understand the differences between AI, Machine Learning, and Deep Learning, and where each fits in solving real-world problems.
Learn supervised and unsupervised learning techniques, along with classification, clustering, and regression.
Discover how to identify the most suitable machine learning technique for different business and technical use cases.
Explore popular machine learning platforms and frameworks, including TensorFlow, Amazon Machine Learning, Azure Machine Learning, Spark MLli
Understand the data science lifecycle, the relationship between data engineering and data science, and the role of quality data.
AI vs ML vs DL Key concepts and terminology Real-world examples
Supervised learning Unsupervised learning Classification, regression, and clustering Selecting the right algorithm
Data science process Data engineering vs data science Importance of data quality and preparation
TensorFlow Amazon Machine Learning Azure Machine Learning Spark MLlib Python and R ecosystem
Industry use cases Business applications When to use—and not use—machine learning
Roles and responsibilities Project planning Best practices for ML adoption

CEO BigDataTrunk.com , Academy360.ai &Certify360.ai | Author
Beginners interested in AI and Machine Learning
Business Analysts and Decision Makers
Data Engineers and Analytics Professionals

Live sessions
Learn directly from Academy360.ai in a real-time, interactive format.
Access to e-Learning courses
Students get 3 months access to relevant courses on Academy360.ai
Certificate of completion
Share your new skills with your employer or on LinkedIn.
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11:30am–2:30pm EDT