AI & Machine Learning Training

For Teams and Professionals

Learning Goals

This curriculum enables learners to:

1

Understand the foundations of AI, machine learning, and deep learning

2

Build and deploy large language model (LLM) applications

3

Apply prompt engineering and RAG techniques for enterprise use cases

4

Develop computer vision and NLP solutions using modern frameworks

5

Implement MLOps practices for production-grade AI systems

6

Design AI agents and automation workflows

7

Evaluate AI ethics, security, and governance frameworks

8

Deliver an end-to-end AI capstone project

Training Modules

1

Foundations of AI & Machine Learning

AI landscape overview, supervised vs unsupervised learning, neural network fundamentals, model training lifecycle, key frameworks (TensorFlow, PyTorch)

2

Data Engineering for AI

Data collection and preprocessing, feature engineering, data pipelines, handling imbalanced datasets, data versioning and governance

3

Natural Language Processing (NLP)

Text preprocessing, tokenization, embeddings, sentiment analysis, named entity recognition, text classification, transformer architecture

4

Large Language Models (LLMs)

GPT, Claude, and LLaMA architectures, prompt engineering, fine-tuning, RAG (Retrieval-Augmented Generation), context windows, token optimization

5

Generative AI Applications

Text generation, image generation (Stable Diffusion, DALL-E), code generation, AI agents, multi-modal models, responsible AI practices

6

Computer Vision

Image classification, object detection, image segmentation, CNNs, transfer learning, real-time video analysis, edge deployment

7

AI in the Enterprise

AI strategy and roadmap, use case identification, ROI assessment, change management, AI governance frameworks, compliance and ethics

8

Prompt Engineering & AI Integration

Advanced prompting techniques, chain-of-thought, few-shot learning, API integration, building AI-powered applications, tool use and function calling

9

MLOps & Model Deployment

Model versioning, CI/CD for ML, containerization, cloud deployment (AWS SageMaker, Azure ML, GCP Vertex AI), monitoring and drift detection

10

AI Agents & Automation

Autonomous agents, multi-agent systems, workflow automation, tool integration, memory and planning, agent frameworks (LangChain, CrewAI)

11

AI Security & Responsible AI

Adversarial attacks, prompt injection, model safety, bias detection and mitigation, explainability (XAI), regulatory compliance

12

Capstone Project & Certification

End-to-end AI solution design, team-based project, real-world dataset application, presentation and peer review, certification assessment

Training Is Just the Beginning

This AI & ML curriculum powers the Accelerate phase of USSP's end-to-end AI Transformation framework. Combine training with readiness assessment, strategy, and talent staffing for a complete AI adoption journey.

Explore AI Transformation Services

Contact Us

For Availability, Pricing and Customization options

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Chicago IL 60614

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Phone: +1-(312) 546-4306

Fax: +1-(312) 253-2026

accounts@ussoftwarepro.com