Foundations of AI and Machine Learning for Java Developers

Course details

In this course, explore the exciting world of artificial intelligence (AI) and machine learning (ML) from a Java developer’s perspective. Start with the essential principles of AI/ML and why patterns are so important. Learn how to differentiate between AI, ML, and deep learning, and clearly understand predictive AI versus generative AI. Join instructor Frank Greco to build a solid foundation on how to use ML in your software development projects and processes effectively.

Learning objectives
Summarize the foundational concepts of machine learning and artificial intelligence.
Recognize the value and importance of patterns in machine learning.
Differentiate between artificial intelligence, machine learning, and deep learning.
Compare and contrast predictive AI and generative AI.
Identify appropriate applications of machine learning in the software development process.

Concepts

0. Introduction

01 - Transform your Java skills with machine learning
02 - What you should know

1. Patterns - The Foundations of Machine Learning

03 - Design patterns
04 - Patterns are everywhere
05 - Regular expressions and the relationship to ML
06 - Machine learning definition

2. Artificial Intelligence Taxonomy

07 - High-level description of AI and ML
08 - Definition of deep learning - PredAI and GenAI
09 - Predictive AI vs. generative AI

3. Predictive AI with JSR #381

10 - JSR #381 - Visual Recognition (VisRec)
11 - Sample VisRec code to train a PredAI model
12 - Sample VisRec code to use a PredAI model
13 - Demo - Running VisRec JSR #381

4. Generative AI

14 - Large language models and NLP
15 - Prompts and completions
16 - Prompt tips
17 - Importance of context
18 - Retrieval-augmented generation (RAG)
19 - Different ways of using LLMs

5. GenAI Services and APIs

20 - Available GenAI LLM services
21 - Accessing LLMs via stateless REST APIs
22 - Approaches and Java REST libraries
23 - Code examples of connecting to an LLM - Pure Java and LC4J
24 - Demo - Connecting to an LLM

6. Patterns in Software Development

25 - Patterns in the software development process
26 - Determinism vs. probability
27 - AI flowchart

Conclusion

28 - Your new tools - Predictive AI and generative AI