AI & ML Training Paths

Instructor-led training paths for business teams, at up to 75% less than enterprise providers. Each path is delivered live and adapted to the tools your team already uses.

Upskilling and reskilling non-technical staff

Not everyone who needs to understand AI is going to build it. The paths below run from beginner to advanced, so a group of product managers, analysts or support leads can start at the foundations while your engineers take the deeper technical tracks.

For a small or mid-sized company that usually means one or two days for the wider team and a longer path for the people shipping the work. Tell us the mix when you enquire and we will scope it accordingly — pricing is per training day, so a broad session costs the same for five people as for ten.

GenAI Expertise

Master generative AI from prompt engineering to production deployment

Duration: 4 weeks•5 courses

Course Curriculum

#1Prompt Engineering BasicsBeginner

2 days • Business Users, Product Managers

Master effective prompting techniques for ChatGPT, Claude, and other LLMs.

Key Modules:
  • •Prompt Structure
  • •Context Setting
  • •Chain of Thought
  • •Output Formatting

#2Advanced Prompt EngineeringPractitioner

3 days • AI Product Managers, Prompt Engineers

Complex prompting patterns, multi-shot learning, and prompt optimization strategies.

Key Modules:
  • •Few-shot Learning
  • •Prompt Templates
  • •Prompt Chaining
  • •Performance Optimization
Prerequisites: Prompt Engineering Basics

#3LLM Integration PatternsIntermediate

4 days • Software Engineers, Solution Architects

Integrate OpenAI, Anthropic, and other LLM APIs into production applications.

Key Modules:
  • •API Integration
  • •Error Handling & Retries
  • •Cost Optimization
  • •Security Best Practices
Prerequisites: Advanced Prompt Engineering

#4RAG Systems DevelopmentIntermediate

5 days • ML Engineers, Backend Developers

Build retrieval-augmented generation systems with vector databases and embedding models.

Key Modules:
  • •Vector Embeddings
  • •Similarity Search
  • •Document Processing
  • •RAG Architecture Patterns
Prerequisites: LLM Integration Patterns

#5Fine-tuning & RLHFAdvanced

6 days • ML Engineers, AI Researchers

Fine-tune LLMs with custom datasets and implement reinforcement learning from human feedback.

Key Modules:
  • •Fine-tuning Strategies
  • •Dataset Preparation
  • •RLHF Implementation
  • •Model Evaluation
Prerequisites: RAG Systems Development

Agentic AI with MCP

Build autonomous AI agents with Microsoft Copilot Platform

Duration: 5 weeks•5 courses

Course Curriculum

#1Agents & MCP FrameworksIntermediate

4 days • Senior Developers, AI Engineers

Build autonomous AI agents using Microsoft Copilot Platform and similar frameworks.

Key Modules:
  • •Agent Architecture
  • •MCP Framework
  • •Tool Integration
  • •Multi-agent Systems

#2Advanced RAG & MemoryAdvanced

5 days • AI Architects, Senior Engineers

Implement sophisticated memory systems and advanced RAG patterns for intelligent agents.

Key Modules:
  • •Long-term Memory
  • •Contextual Retrieval
  • •Hybrid Search
  • •Memory Management
Prerequisites: Agents & MCP Frameworks

#3Agent Reasoning & PlanningAdvanced

4 days • AI Researchers, Lead Engineers

Implement reasoning engines and planning algorithms for autonomous decision-making.

Key Modules:
  • •Reasoning Frameworks
  • •Planning Algorithms
  • •Decision Trees
  • •Goal-oriented Agents
Prerequisites: Advanced RAG & Memory

#4Production Agent SystemsAdvanced

5 days • Platform Engineers, DevOps

Deploy, monitor, and scale agent systems in production environments.

Key Modules:
  • •Agent Orchestration
  • •Monitoring & Observability
  • •Security & Compliance
  • •Performance Optimization
Prerequisites: Agent Reasoning & Planning

#5Multi-Agent OrchestrationAdvanced

6 days • System Architects, AI Leaders

Design and implement complex multi-agent systems with coordination and communication protocols.

Key Modules:
  • •Agent Communication
  • •Coordination Protocols
  • •Distributed Systems
  • •Swarm Intelligence
Prerequisites: Production Agent Systems

AI/ML Expertise

Comprehensive machine learning and deep learning mastery

Duration: 7 weeks•6 courses

Course Curriculum

#1Data Science FoundationsBeginner

5 days • Business Analysts, Junior Data Scientists

Essential data science concepts, Python programming, and statistical analysis fundamentals.

Key Modules:
  • •Python for Data Science
  • •Statistics & Probability
  • •Data Wrangling with Pandas
  • •Exploratory Data Analysis

#2Applied Machine LearningPractitioner

7 days • Data Scientists, ML Engineers

Hands-on machine learning with scikit-learn, covering classification, regression, and clustering.

Key Modules:
  • •Supervised Learning
  • •Unsupervised Learning
  • •Feature Engineering
  • •Model Evaluation & Selection
Prerequisites: Data Science Foundations

#3Deep Learning FundamentalsIntermediate

6 days • ML Engineers, Research Scientists

Neural networks, CNNs, and RNNs with TensorFlow and PyTorch.

Key Modules:
  • •Neural Network Architecture
  • •Convolutional Neural Networks
  • •Recurrent Neural Networks
  • •Deep Learning Optimization
Prerequisites: Applied Machine Learning

#4NLP FoundationsIntermediate

5 days • Data Scientists, NLP Engineers

Text processing, embeddings, and traditional NLP techniques.

Key Modules:
  • •Text Preprocessing
  • •Word Embeddings
  • •Named Entity Recognition
  • •Sentiment Analysis
Prerequisites: Applied Machine Learning

#5Transformers & LLMsAdvanced

8 days • Senior ML Engineers, AI Researchers

BERT, GPT architectures, fine-tuning, and prompt engineering for large language models.

Key Modules:
  • •Transformer Architecture
  • •BERT & GPT Models
  • •Fine-tuning Strategies
  • •Prompt Engineering
Prerequisites: NLP Foundations, Deep Learning Fundamentals

#6MLOps & ProductionAdvanced

4 days • ML Engineers, DevOps Engineers

Deploy and monitor ML models at scale with MLflow, Kubernetes, and cloud platforms.

Key Modules:
  • •Model Versioning
  • •CI/CD for ML
  • •Model Monitoring
  • •A/B Testing & Deployment
Prerequisites: Deep Learning Fundamentals

🚀 Fast Track Option: ML Fast Track Workshop

Intensive hands-on workshop covering ML essentials in 10 days.

10 days intensive workshop • Replaces first 3 courses

🎓 Advanced Specialization: Data Science Mastery Bundle

Complete advanced specialization bundle for mastery-level expertise.

IntermediateComputer Vision
IntermediateReinforcement Learning
IntermediateHands-on NLP
AdvancedTransformers
AdvancedEnsemble Models
AdvancedTime Series Advanced
AdvancedAutoML & HPO

15 days • $43,875$48,750

AI Development

Full-stack development skills for AI applications

Duration: 4 weeks•4 courses

Course Curriculum

#1Python for AI DevelopmentBeginner

5 days • Developers new to Python

Python fundamentals with focus on AI/ML libraries and best practices.

Key Modules:
  • •Python Syntax & Features
  • •NumPy & Pandas
  • •Async Programming
  • •Testing & Debugging

#2API Development for AIPractitioner

4 days • Backend Developers

Build robust APIs for AI services using FastAPI, async patterns, and best practices.

Key Modules:
  • •FastAPI Framework
  • •Async/Await Patterns
  • •API Security
  • •Performance Optimization
Prerequisites: Python for AI Development

#3Cloud AI ServicesIntermediate

5 days • Cloud Engineers, DevOps

Deploy AI applications on AWS, Azure, and GCP with managed AI services.

Key Modules:
  • •Cloud AI Services
  • •Serverless AI
  • •Container Orchestration
  • •Cost Management
Prerequisites: API Development for AI

#4Full-Stack AI ApplicationsIntermediate

6 days • Full-Stack Developers

Build end-to-end AI applications with React, Next.js, and AI backend services.

Key Modules:
  • •React for AI UIs
  • •Real-time Updates
  • •State Management
  • •AI-powered Features
Prerequisites: API Development for AI

Infrastructure & DevOps Bundles

Docker & Kubernetes Bundle

Complete containerization and orchestration

10 days •5 courses
$26,000$32,500Save 20%
Terraform & IaC Bundle

Infrastructure as code expertise

8 days •4 courses
$23,375$27,500Save 15%
Airflow & Orchestration Bundle

Master workflow orchestration

6 days •3 courses
$18,000$20,000Save 10%
Kafka & Streaming Bundle

Real-time data streaming

5 days •2 courses
$15,000

Volume Pricing & Discounts

The more you learn, the more you save!

Base Rate

  • • $3,000 per training day
  • • Up to 10 students included
  • • No minimum seat requirement
  • • Course materials included

Volume Discounts

  • • Scaled by total student-days
  • • Larger teams save more
  • • Longer programs save more
  • • Up to 20% off

Payment Terms

  • • Net 30: Standard pricing
  • • Net 0: 5% discount
  • • 50% prepaid: 10% discount
  • • 100% prepaid: 15% discount

Up to up to 75% less than enterprise training costs!

Loading course catalog...

Training for specific teams

Some teams need a path built around their day-to-day work rather than a general AI curriculum.

AI Training for Customer Support Teams

Build support agents grounded in your own help centre, with escalation design and evaluation from real tickets. 7 days, from $3,000/day.

AI & ML Training Paths for Business Teams | Data Trainers