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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
- An understanding of machine learning concepts
- Python programming experience
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
That it was applying real company data. Trainer had a very good approach by making trainees participate and compete
