Certified AI Professional (CAIPro)

Certified AI Professional (CAIPro)

Instructor:Nasser Rahal
Latest update:2018-12-01

In this course, participants will get an introduced to AI and the Opportunities Enabled the technology. First, the course will explain the underlying technologies and tools, then we will dig into the applications such as: Sales and Marketing, Manufacturing and supply-chain, etc… The second part of the course will focus on how to create innovative products driven by data and algorithms. Finally, we will cover the topic of how to design organization structures and business models to leverage data and algorithms, machine learning, and deep learning.


Intro to AI and the Opportunities Enabled the technology

  • Use-cases with specific business impacts
  • What is AI? - hype versus reality
  • What is Machine Learning
  • What is Deep Learning
  • Trends in AI
  • How does AI work?
  • How does Deep Learning Models learn?

Applications in in Sales and Marketing

  • Technology merges the Sales & Marketing channel into a unified customer journey
  • Addressing new customers: customer profiling and mass message customization to lookalike audiences
  • Converting customers: from recommender engines to sales team management solutions
  • Contracting with customer: CRM based recommendation (B2B), and e-commerce closing boost (shopping assistants and search engines in B2C)
  • Delighting the customer: monitoring and reacting to market feedback, predicting churn

Applications in Manufacturing and Supply Chain management

  • Data driven supply chain that drives horizontal integration with buyers and suppliers
  • Reducing inventory and transportation costs with big data analysis: from demand forecasting to route and inventory optimization
  • AI in Industry 4.0

AI applications in Customer service HR

  • Boosting zero level support: chatbots and intelligent search engines
  • Managing the customer service team: from transcripts to voice sentiment analysis and predictions
  • The recruitment revolution: from targeting passive talents to CV processing and video interviews
  • On-boarding assistance with robotic process automation and chatbots
  • Talent management, knowledge management and employee churn management with network analysis and natural language processing

Applications in Legal, Finance and Back-office

  • Processing contracts for sensitive clauses with NLP
  • Identifying sensitive information for GDPR compliance with pattern recognition
  • Improving audit with processing invoices at scale
  • The SSC automation opportunity: robotic and cognitive process automation


Building a data driven organization

  • Data as the source of insight
  • Maturity model of a digital company
  • AI Models and Algorithms on the digitization scale

Working with AI projects

  • The Data - Technology - Business KPI triangle
  • Make or buy dilemma: providers, start-ups, platforms, developers
  • Evaluating project opportunities within your organization: pain points, data source, stakeholders, impacts, quick wins

Intro to the machine learning canvas

  • Managing the Training data and AI Models capital
  • Understanding the Business problem
  • New roles in an organization: data manager, data engineer, data scientist
  • Dilemmas of the place of the data team in the organization or project
  • Descriptive, predictive, prescriptive analytics
  • The layers of data management: big data, data cleaning, validation
  • Setting up the team for a first project

Building the learning cycle

  • How does an AI learn - teaching data and feedback loop
  • Assisted intelligence - helping people not replacing them
  • How does an organization learn - system theory, mental models, controlled experiment and reflection loop
  • Cooperating with a new type of intelligence - the culture of adapting the technology driven future at scale
  • Designing the implementation process and quick wins


Capstone Project: Presenting and winning an AI project


Learning Experience at Lassonde Professional Development (LPD), York University