AI Strategy and Implementation Training for Technical Project Managers: Navigating the AI Lifecycle

Module 1: Foundations of AI and ML for Project Leaders

ü  Understanding the difference between AI, Machine Learning, and Deep Learning

ü  Key terminology: Neural Networks, Algorithms, and Training Sets

ü  Overview of Supervised, Unsupervised, and Reinforcement Learning

ü  Current industry trends and the "AI Hype" vs. Reality

ü  Practical Session: Mapping business problems to specific AI/ML categories.

Module 2: The AI Project Lifecycle and Feasibility Assessment

ü  Defining the "Discovery Phase" for AI projects

ü  Assessing technical feasibility and data availability

ü  Calculating ROI and defining Success Metrics (KPIs) for AI

ü  Identifying "Low Hanging Fruit" vs. Moonshot AI projects

ü  Practical Session: Developing an AI Project Charter and Business Case.

Module 3: Data Strategy and Infrastructure for Project Managers

ü  The role of Big Data in AI success

ü  Data collection, labeling, and cleaning workflows

ü  Understanding Data Pipelines and ETL (Extract, Transform, Load)

ü  Cloud vs. On-premise infrastructure for AI workloads

ü  Practical Session: Creating a Data Readiness Checklist for a sample project.

Module 4: Managing Data Science Teams and Talent

ü  The anatomy of an AI team: Data Scientists, ML Engineers, and Data Architects

ü  Bridging the communication gap between "Business" and "Code"

ü  Managing research-heavy tasks vs. production-heavy tasks

ü  Resource allocation and preventing "Burnout" in high-complexity projects

ü  Practical Session: Role-playing stakeholder meetings to explain model limitations.

Module 5: Agile Methodologies for AI Development

ü  Why traditional Scrum fails for AI and how to adapt it

ü  Kanban vs. Scrum for experimental data science

ü  Managing "Sprints" when research outcomes are uncertain

ü  Iterative model improvement cycles

ü  Practical Session: Designing a 2-week Sprint plan for a model training phase.

Module 6: Ethics, Bias, and Governance in AI Implementation

ü  Identifying and mitigating algorithmic bias

ü  Data privacy regulations: GDPR and AI Acts

ü  Explainable AI (XAI): Why the "Black Box" is a risk

ü  Developing an Ethical AI Framework for your organization

ü  Practical Session: Conducting an AI Ethics Impact Assessment on a case study.

Module 7: Integrating LLMs and Generative AI into Products

ü  Understanding LLM architectures and "Prompt Engineering"

ü  RAG (Retrieval-Augmented Generation) vs. Fine-tuning

ü  Managing costs and token usage in Generative AI projects

ü  Risk management: Hallucinations and data leakage

ü  Practical Session: Building a roadmap for integrating a chatbot using LLM APIs.

Module 8: Quality Assurance and Testing for AI Models

ü  The difference between Software QA and AI Model Validation

ü  Understanding Accuracy, Precision, Recall, and F1-Score

ü  User Acceptance Testing (UAT) for probabilistic systems

ü  Unit testing for data pipelines

ü  Practical Session: Reviewing a model performance report to decide on "Go/No-Go" for deployment.

Module 9: Deployment (MLOps) and Performance Monitoring

ü  Introduction to MLOps: The DevOps of Artificial Intelligence

ü  Version control for data and models

ü  Monitoring "Model Drift" and performance decay over time

ü  Scaling AI solutions from Pilot to Production

ü  Practical Session: Designing a post-deployment monitoring dashboard.

Module 10: Strategic AI Scaling and Change Management

ü  Creating an AI Center of Excellence (CoE)

ü  Overcoming organizational resistance to AI adoption

ü  Upskilling existing staff and fostering an AI-ready culture

ü  Long-term maintenance and technical debt in AI

ü  Practical Session: Developing a 12-month AI Strategic Roadmap for an organization.

About Our Trainers

Our trainers are veteran Technology Leaders and Certified Project Management Professionals (PMP) with extensive experience in leading AI transformations for Fortune 500 companies. They bring a unique blend of technical expertise in Python/ML and strategic leadership, having successfully delivered projects ranging from predictive maintenance systems to enterprise-grade Generative AI implementations.

Quality Statement

Phoenix Training Center is dedicated to delivering high-caliber, industry-relevant education. Our AI curriculum is developed in collaboration with active AI practitioners to ensure that the strategies taught are currently applicable in the global tech market. We emphasize practical utility over pure theory to ensure immediate workplace impact.

Tailor-Made Courses

We understand that every organization has unique challenges and opportunities as well as unique training needs. Phoenix Training Center offers tailor-made courses designed to address specific requirements and challenges faced by your team or organization. Whether you need a customized curriculum, a specific duration, or on-site delivery, we can adapt our expertise to provide a training solution that perfectly aligns with your objectives. We can customize this Course to focus on your industry, specific risk profile, or internal stakeholder dynamics. Contact us to discuss how we can create a bespoke training program that maximizes value and impact for your team. For further inquiries, please contact us on Tel: +254720272325 / +254737296202 or Email training@phoenixtrainingcenter.com

Admission Criteria

ü  Participants should be reasonably proficient in English. 

ü  Applicants must live up to Phoenix Center for Policy, Research and Training admission criteria.

Terms and Conditions

ü  Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

ü  What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

ü  Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

ü  The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

ü  Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@phoenixtrainingcenter.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training. Or call us on +254720272325 / +254737296202

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

ü  Groups of 5 People and Above – Cheque Payments to: Phoenix Center for Policy, Research and Training Limited should be paid in advance, 5 days to the training.

ü  Invoice: We can send a bill directly to you or your company.

ü  Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

ü  Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

ü  Participants may cancel attendance 14 days or more prior to the training commencement date.

ü  No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Accommodation and Airport Transfer

For physical training attendees, we can assist with recommendations for accommodation near the training venue. Airport pick-up services can also be arranged upon request to ensure a smooth arrival. Please inform us of your travel details in advance if you require these services. For reservations contact the Training Officer on Email: training@phoenixtrainingcenter.com or on Tel: +254720272325 / +254737296202