Course

Credit Type:
Course
ACE ID:
DLAI-0001
Version:
2
Organization:
Deeplearning AI
Location:
Online
Length:
Approximately 5 months to complete at 8 hours/week
Minimum Passing Score:
80
ACE Credit Recommendation Period:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Lower-Division Baccalaureate 3 Fundamentals of Neural Networks and Deep Learning
Upper-Division Baccalaureate 3 Applied Techniques in Machine Learning Systems
Upper-Division Baccalaureate 3 Deep Learning Architectures
Description

Objective:

This course is offered through Coursera, which is an ACE Authorized Instructional Platform.

The course objective is to provide an understanding of the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.

Learning Outcomes:

  • Learn how LLMs work. By knowing how machine learning systems work, you’ll be able to use them more effectively to support your work as a developer
  • Optimize your code quality. Get to production-ready code faster by working with an LLM to find and fix bugs
  • Experiment quickly. Using LLMs can speed up your ability to prototype and test new features, allowing you to quickly iterate and ship your code
  • Team up with AI on engineering tasks. Break through roadblocks and with your team by leveraging an LLM’s knowledge of development roles and tasks

General Topics:

  • Introduction to Deep Learning Neural Networks Basics Shallow Neural Networks Deep Neural Networks Practical Aspects of Deep Learning Optimization Algorithms Hyperparameter Tuning, Batch Normalization and Programming Frameworks Introduction to ML Strategy Foundations of Convolutional Neural Networks Deep Convolutional Models: Case Studies Object Detection Special Applications: Face Recognition and Neural Style Transfer Recurrent Neural Networks Natural Language Processing and Word Embeddings Sequence Models and Attention Mechanism Transformer Network
Instruction & Assessment

Instructional Strategies:

  • Audio Visual Materials
  • Case Studies
  • Lectures
  • Practical Exercises

Methods of Assessment:

  • Other
  • Quizzes
  • Programming assignment
Supplemental Materials
Equivalencies