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Course Outline
Introduction
- Overview of Machine Learning (ML) and Deep Learning (DL) concepts.
- Future industry evolutions with ML and DL.
Business Strategy with Deep Learning
- Defining business problems.
- Data-driven decision making.
- Analytical thinking and mindset.
- Business strategy modeling.
- Case studies and examples.
Deep Learning Software and Tools
- Python and Pandas fundamentals.
- DL open source tools (TensorFlow, CNTK, Torch, Keras, etc.).
- Use cases and examples.
Deep Learning with Neural Networks
- Neural Network Learning (Backpropagation).
- Convolutional Neural Network (CNN).
- Recurrent Neural Network (RNN).
- DL modeling examples.
Summary and Next Steps
Requirements
- A solid understanding of machine learning concepts.
- Practical experience with Python programming.
Audience
- Business analysts.
- Data scientists.
- Developers.
14 Hours
Testimonials (3)
I really liked the end where we took the time to play around with CHAT GPT. The room was not set up the best for this- instead of one large table a couple of small ones so we could get into small groups and brainstorm would have helped
Nola - Laramie County Community College
Course - Artificial Intelligence (AI) Overview
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Department of Jobs, Regions, and Precincts
Course - Artificial Neural Networks, Machine Learning, Deep Thinking
It felt like we were going through directly relevant information at a good pace (i.e. no filler material)
