Cognilytica Training

Cognilytica AI & ML Project Management

Training & Certification

The Leading Vendor Independent, AI & ML Project Management Training

Cognilytica’s AI & ML Project Management Certification Boot Camp is recognized around the world as one of the best AI & ML as related to Project Management training course available anywhere.

The Boot Camp is an intensive, three day “fire hose” of information that prepares you to succeed with your AI & ML efforts, whether you’re just beginning them or are well down the road with implementation. Cognilytica’s training is the only public course that Cognilytica offers, reflecting the best thinking and research that Cognilytica produces.

Cognilytica’s AI & ML Project Management Certification has no prerequisites, and is designed for people managing AI & ML projects but appropriate for people with different roles and levels of expertise.  This course is valuable for anyone who wants in-depth knowledge about how to succeed with AI & ML related projects.

  What makes the Cognilytica Training so special?

  • Vendor independent
  • End User focused
  • Updated up to six times  year
  • AI & ML Project Management Focused
  • Provides the enterprise context
  • Offers detailed case studies
  • Globally recognized certification
  • Led by AI & ML thought leaders
  • Not too technical, not too high-level
  • Includes certification

Interesting in enrolling? Contact us!

Highlights of Cognilytica AI & ML Project Management Training & Certification

  • AI Approaches

  • The AI-Enabled Vision of the Future
  • Augmented Intelligence as a first Approach
  • The Intelligent Assistant
  • Applications of ML

  • Goals of Machine Learning
  • ML Anti-Patterns
  • Case Studies in ML
  • ML Model training
  • Responsible AI / XAI
Not Just Theory!

The course includes several case studies written by enterprise practitioners, as well as an in-depth look at AI/ML Implementation Plan.

How Does Cognilytica Compare?



Code AcademiesVendor Training
3-day Course Price
(US Events, per person)




Certification & Exam Cost     







Implementation Focused


Developer FocusedMarketing Focused
Certification Granted in Course


Content Updated

4-6 times a year

1-2 times a year???
Taught by Recognized Experts


Hired instructorsTaught by Marketing or Product People

Cognilytica AI & ML Project Management Training & Certification is offered as public and private courses, as well as custom-designed courses for your specific and special needs!

Interesting in enrolling? Contact us!

Agenda v.2.3

Module 1: Setting the Bar – AI, ML, and Data Science
  • Goals of Artificial Intelligence (AI)
  • How did we get here? A Brief History of AI
  • The AI-Enabled Vision of the Future
  • Goals of Machine Learning (ML)
  • Why is ML Necessary?
  • Relationship between ML and Data Science
  • Predictive and Projective Analytics vs. ML
  • Introducing The DIKUW Pyramid (formerly, the DIKW Pyramid)
Module 2: Applications of AI and ML
  • Applications of ML: Semantic Recommendations
  • Applications of ML: Interpretability
  • Applications of ML: Probabilistic Programming
  • Applications of ML: Summarization
  • Applications of ML: Image Recognition, Classification, and Analysis
  • Applications of ML: Natural Language Processing & Generation (NLP / NLG)
  • Applications of ML: Chatbots
  • Applications of ML: Advanced Robotics
  • Case Studies in ML: Real-World Examples
Module 3: Approaches to AI and ML
  • AI Approaches: Knowledge Graphs
  • AI Approaches: Neural Networks
  • AI Approaches: Neural Networks — Deep Learning
  • AI Approaches: Evolutionary Algorithms
  • AI Approaches: Reinforcement Learning
  • AI Approaches: Generative Adversarial Networks (GANs)
Module 4: Advanced Analytics & Statistics / ML Anti-Patterns
  • Data Science in the Context of ML
  • Fundamental Data Science requirements for ML
  • Linear & Logistic Regressions as Predictions
  • T-SNE and Data Clustering
  • Nearest-neighbor Approaches
  • ML Anti-Patterns: Predictive Analytics & Statistics (Good, but not ML)
  • Intelligent Process Automation vs. Robotic Process Automation
  • ML Anti-Patterns: Automation is not Intelligence
Module 5: AI & ML Project Management — Planning
  • AI & ML Project Management is NOT Like Application Development Project Management
  • ML Projects are Data Management and Processing Projects
  • ML Project planning: Data requirements
  • Unstructured vs. Structured Data
  • ML Pre-project necessities: Cleaning Data
  • ML Model training: Supervised Learning
  • ML Model training: Unsupervised Learning
Module 6: AI & ML Project Management — Scoping & Staffing
  • ML Scoping: Picking the right algorithms
  • ML “Platforms” and Tooling
  • ML Project Scoping: AI / ML Project Staging – Waterfall and Agile Approaches Don’t Apply?
  • ML Project staging: The PoC vs. the Pilot
  • Using the DIKUW Pyramid to find the Sweet Spot
  • Augmented Intelligence as a first Approach
  • Intelligent Assistant Projects
  • Intelligent Process Automation Projects
  • ML Project Staffing: Data Scientists vs. Data Engineers
Module 7: Responsible AI / ML
  • AI & ML Ethics Considerations
  • Avoiding Bias in ML Training Data
  • Malicious AI & Adversarial AI
  • Cybersecurity for / with AI
  • Explainable AI (XAI)
  • XAI: AI & Blockchain

Interesting in enrolling? Contact us!