AI Application Development Specialization
Issued by
UCSC Silicon Valley Extension
Students utilized AI Application Development skills in deep learning for data manipulation, statistical analysis, and modeling. They explored the business implications and opportunities associated with AI and how to harness the technology with process integration and enhanced workflows. They built deep learning prediction models from linear logistic regression to categories of neural networks. Students selected an advanced area of study (RL, NLP, GANs) in the industry-oriented capstone project.
- Type Learning
- Level Advanced
- Time Months
- Cost Paid
Skills
- AI
- AI Applications
- AI Integration And Implementation
- Application Development
- Applications Of Artificial Intelligence
- Artificial Intelligence
- Artificial Neural Networks
- Convolutional Neural Network (CNN)
- Convolutional Neural Networks (CNNs)
- Data Engineering
- Data Manipulation
- Data Science
- Data Synthesis
- Deep Learning
- Enterprise AI Applications
- Generative Adversarial Networks
- Generative Adversarial Networks (GANs)
- Keras
- Logistic Regression
- Long Short-Term Memory (LSTM)
- Long Short-Term Memory (LSTMs)
- Machine Learning
- Natural Language Processing
- Natural Language Processing (NLP)
- Natural Language Processing Systems
- NLP
- Predictive Modeling
- Process Integration
- Python
- Recurrent Neural Networks (RNN)
- Recurrent Neural Networks (RNNs)
- Reinforcement Learning
- Reinforcement Learning (RL)
- Robotics
- Software Development
- Statistical Analysis
- TensorFlow
- Workflow Management
Earning Criteria
-
Completed the following courses: The Business of AI; Deep Learning and Artificial Intelligence; One advanced elective (Artificial Intelligence for Robotics; Deep Reinforcement Learning; Natural Language Processing; or GANs for Data Synthesis); and Building Integrated AI Applications. Met all requirements for AI Application Development Specialization. Earned 9.5 CEUs.