PMI-CPMAI™ Exam Preparation Course

Course Objectives

• Equip participants with a comprehensive understanding of AI fundamentals, machine learning concepts, and the PMI-CPMAI methodology to confidently prepare for the Certified Project Management in Artificial Intelligence (PMI-CPMAI) exam.

• Enable learners to apply best practices in AI project management, including aligning AI initiatives with business goals, managing data, developing and evaluating models, and ensuring ethical deployment.

• Develop skills in identifying AI project risks, addressing common pitfalls (e.g., data drift, overfitting), and implementing trustworthy AI principles to achieve successful outcomes in real-world scenarios.

• Prepare participants to pass the PMI-CPMAI exam by mastering exam content, including scenario-based questions, key terminology, and practical applications.

• Foster a forward-thinking approach to AI trends, such as generative AI and large language models, while emphasizing iterative and data-centric project management.

Course Requirements

• Access to a computer with internet for interactive exercises, simulations, and optional tools like Jupyter Notebooks or Google Colab.

• Active participation in group discussions, case studies, and hands-on activities; no prior AI experience is necessary, as the course builds from fundamentals.

Target Audience

• Project managers and IT professionals seeking to specialize in AI-driven projects.

• Business leaders, consultants, and analysts interested in integrating AI into organizational strategies.

• Aspiring AI project managers aiming for PMI-CPMAI certification to advance their careers.

• Professionals in industries like healthcare, finance, retail, or tech who want to leverage AI for efficiency and innovation.

• Anyone with a background in project management or technology looking to bridge the gap between traditional PM and AI methodologies.

Duration : 4 days (approximately 6-8 hours per day, including breaks).

Study Materials: Study Materials: Softcopy (Slides, practice questions, case studies). Official PMI resources are referenced via links.

Syllabus

The syllabus is structured across three days, aligning closely with the PMI-CPMAI methodology by emphasizing its six phases while integrating foundational AI concepts, machine learning, data management, and trustworthy AI. Each day includes lectures, hands-on exercises, case studies, and quizzes for reinforcement. This course is a conceptual AI project management course.

Day 1 – Introduction, AI Fundamentals, and Business Understanding

Focus: Foundation of AI concepts, CPMAI framework overview, and business alignment (Phase I)

Topics:

• Introduction to CPMAI: Certification overview, methodology structure, and its role in AI project success.

• What is AI?: Definitions, history, myths, core components (perception, prediction, planning), and distinctions (Narrow AI vs. AGI).

• The Application of AI: Seven AI patterns (Conversational, Predictive Analytics, Autonomous Systems, etc.) and when to apply AI vs. automation.

• Best Practices and Methodologies for Successful AI Implementation: Common pitfalls, iterative methods (Agile, Lean), and CPMAI alignment.

• Business Understanding Best Practices (CPMAI Phase I): Feasibility analysis, Go/No-Go decisions, stakeholder alignment, and success criteria.

• Hands-On: Mini case study – identifying AI opportunities and aligning them with business goals.

• Daily Quiz & Review: Focus on AI fundamentals, CPMAI structure, and business understanding concepts.

Day 2 – Machine Learning Fundamentals and Core Algorithms

Focus: Building a solid understanding of ML principles, algorithms, and practical modeling.

Topics:

• Machine Learning Fundamentals: Core concepts (supervised, unsupervised, reinforcement learning), deterministic vs. probabilistic models, and feature engineering.

• Machine Learning Algorithms – Part 1: Naive Bayes, KNN, SVM, Decision Trees, and clustering methods.

• Machine Learning Algorithms – Part 2: Neural networks, deep learning basics, CNNs, RNNs, LSTMs, and ensemble techniques.

• Hands-On: Building and testing simple classification and clustering models using Google Colab or Jupyter Notebook.

• Daily Quiz & Review: Reinforcement of ML concepts, algorithm selection, and connections to CPMAI Phases I–III.

Day 3 – Data Management, Preparation, and Model Development

Focus: Managing and preparing data (Phases II–III), and developing models (Phase IV).

Topics:

• Generative AI, Transformers, and LLMs: Key concepts, architectures, practical use cases, and ethical implications.

• Managing Data for AI: Data quality, governance, metadata, and handling the curse of dimensionality.

• CPMAI Phase II – Data Understanding: Assessing sources, validating data quality, identifying gaps, and planning iterations.

• Data Preparation for AI: Cleansing, labeling, augmentation (including generative AI applications).

• CPMAI Phase III – Data Preparation: Structuring and transforming data for model readiness.

• ML Development Tools and Platforms: Overview of AutoML, TensorFlow, PyTorch, and scikit-learn for rapid prototyping.

• CPMAI Phase IV – Model Development: Algorithm selection, training, validation loops, and hyperparameter tuning.

• Hands-On: Data preparation workshop and small-scale model development exercise.

• Daily Quiz & Review: Emphasis on Phases II–IV and data-to-model pipeline integration.

Day 4 – Model Evaluation, Operationalization, and Trustworthy AI

Focus: Deployment, monitoring, and governance of AI systems (Phases V–VI) plus certification preparation.

Topics:

• Model Evaluation and Testing: Metrics (accuracy, precision, recall, F1-score), overfitting/underfitting detection, and cross-validation.

• CPMAI Phase V – Model Evaluation: Addressing model drift, validating business and technical KPIs, and iterative improvements.

• Model Operationalization: Deployment strategies (batch, streaming, microservices), environment choices (cloud, on-premise).

• CPMAI Phase VI – Operationalization:

  Monitoring pipelines, retraining strategies, and ensuring performance over time.

• Trustworthy AI: Ethics, bias mitigation, explain ability, governance, and compliance (GDPR, AI Act, etc.).

• Agentic AI: Additional material on agentic AI.

• Exam Strategies: Understanding exam structure overview and time‑management strategies, scenario-based question tips, and time management.

• Hands-On: Practice exam simulation, team discussions on trustworthy AI scenarios, and feedback.

• Course Wrap-Up: Final Q&A, certification roadmap, and post-course learning resources.

Course Objectives

This course provides participants with comprehensive knowledge and practical techniques aligned with the PMI Project Management Professional (PMP) framework. By the end of the training, participants will be able to:

• Understand how projects contribute to sustainable business value and organizational strategy.

• Initiate, plan, execute, monitor, and close projects using predictive, agile, or hybrid approaches.

• Strengthen leadership, stakeholder management, and communication skills.

• Optimize project team performance and manage challenges effectively.

• Prepare confidently for the PMP certification exam.

Course Requirements

• Basic understanding of project management concepts.

• Prior experience in managing or participating in projects (recommended).

• Familiarity with business or organizational processes.

Target Audience

• Project Managers and Project Coordinators

• Team Leaders and Functional Managers

• PMP Exam Candidates

• Professionals aiming to enhance their project management capability

Duration : 5 Days (approximately 6-8 hours per day, including breaks)

Study Materials: Softcopy (Slide, Exam Content Outline).

Syllabus

Day 1: Module 1 – Business Environment & Module 2 – Start the Project

• Understanding how projects create and sustain business value.

• Adapting to external dynamics: regulatory, market, and environmental changes.

• Aligning projects with organizational strategy and governance.

• Building a solid project foundation through a Project Charter.

• Identifying stakeholders and defining their needs, influence, and expectations.

• Establishing early communication and alignment of project goals.

Day 2: Module 3 – Plan the Project

• Developing a comprehensive project management plan covering scope, schedule, cost, and quality.

• Planning for risk, communication, procurement, and stakeholder engagement.

• Integrating predictive, agile, or hybrid methodologies appropriately.

• Establishing baselines and performance measurement approaches.

Day 3: Module 4 – Lead the Project Team

• Leading with adaptive and collaborative leadership styles.

• Building, motivating, and developing a high-performing project team.

• Enhancing interpersonal and conflict resolution skills.

• Encouraging a culture of openness, transparency, and accountability.

• Managing stakeholder engagement throughout the project lifecycle.

Day 4: Module 5 – Support the Project Team Performance

• Monitoring ongoing team performance and project progress.

• Applying continuous improvement and feedback mechanisms.

• Managing obstacles, risks, and change requests effectively.

• Maintaining agility, resilience, and team collaboration.

• Using data-driven decision-making to improve outcomes.

Day 5: Module 6 – Close the Project/Phase & PMP Exam Simulation

Module 6: Close the Project/Phase

• Executing professional project closure procedures.

• Capturing lessons learned and ensuring comprehensive documentation.

• Recognizing team achievements and ensuring knowledge transfer.

• Ensuring sustainable business impact and organizational learning.

PMP Exam Simulation

• Full-length PMP-style practice exam.

• Review of key concepts and situational questions.

• Discussion of exam-taking strategies and time management tips.

• Personalized feedback and readiness assessment.

PMP®
Exam Preparation Course

Batch I : 24 Nov 2025

Durasi : 4 hari (09:00-17:00)
Minimum start : 10 peserta**
Lokasi : Jakarta Pusat
2x Coffeebreak & 1x Lunch
35 PDU

Biaya Pendaftaran : Rp 15.000.000,-*

* Pembayaran: DP 30%, pelunasan H-1 sebelum Training
** Jika tidak terpenuhi 100% refund max 3 hari kerja

Training is not affiliated with, sponsored, or endorsed by PMI.
PMI, the PMI logo, PMP, and CPMAI are trademarks of Project Management Institute, Inc.

Batch I : 24 Nov 2025

Durasi : 5 hari (09:00-17:00)
Minimum start : 10 peserta**
Lokasi : Jakarta Pusat
2x Coffeebreak & 1x Lunch
35 PDU

Biaya Pendaftaran : Rp 11.000.000,-*

* Pembayaran: DP 30%, pelunasan H-1 sebelum Training
** Jika tidak terpenuhi 100% refund max 3 hari kerja

Trainer berpengalaman lebih dari 20 tahun di bidang Project Management.

Sertifikasi:
PMP, PMI-PMOCP, PMI-CPMAI, COBIT 2019, Google PM, SAFe Agilist, Design Sprint Practitioner.

Trainer berpengalaman lebih dari 20 tahun di bidang Project Management & 5 tahun dibidang Artificial Intelligence Implementation.

Sertifikasi:
PMP, PMI-PMOCP, PMI-CPMAI, COBIT 2019, Google PM, SAFe Agilist, Design Sprint Practitioner.