In an increasingly data-driven world, the ability to leverage data science is becoming a critical skill for modern project managers. This "Unlocking Insights: Data Science for Project Managers Training Course" is a specialized program designed to bridge the gap between project management and data analytics. This course will empower you to understand data science methodologies, communicate effectively with data teams, and use data-driven insights to make better project decisions, optimize resource allocation, and ultimately, drive successful project outcomes.

Over this intensive 10-day period, you will move from a foundational understanding of data concepts to a practical application of data science principles within your projects. You will learn about the data lifecycle, common machine learning algorithms, and how to interpret project-related data to predict risks, monitor progress, and measure performance. This program is not about turning you into a data scientist, but rather about equipping you with the knowledge to strategically manage data-intensive projects and confidently lead your teams towards data-informed success.

Duration: 10 days

Target Audience:

• Project Managers
• Program Managers
• Business Analysts
• Team Leads
• Scrum Masters
• Product Owners
• Functional Managers
• IT Managers
• Agile Practitioners
• Individuals seeking to manage data-centric projects

Objectives:

• Understand the data science lifecycle and its stages
• Learn to communicate effectively with data scientists and analysts
• Identify key data sources and metrics for project success
• Master data governance and quality control principles
• Use data analytics to forecast project timelines and budgets
• Interpret common data visualizations and statistical models
• Manage risks and uncertainties using data-driven insights
• Understand the ethical considerations of using data in projects
• Learn to build a data-centric project plan
• Measure the business value and ROI of data initiatives

Course Modules:

Module 1: Introduction to Data Science

• The definition of data science and its key components
• The role of data in modern organizations
• The data science lifecycle from a PM's perspective
• The different types of data and their uses
• Key concepts and terminology in data science

Module 2: Data Collection and Preparation

• Identifying and sourcing relevant data
• Understanding data structures and formats
• The importance of data cleaning and preprocessing
• Common challenges in data preparation
• Tools and technologies for data handling

Module 3: Foundational Statistics for PMs

• The basics of descriptive statistics (mean, median, mode)
• Understanding probability and its role in risk assessment
• The concept of statistical significance
• Using data to test hypotheses
• The difference between correlation and causation

Module 4: Data Visualization and Storytelling

• The power of visual data
• Common chart types and their uses
• Creating effective and clear dashboards
• Telling a story with data to influence stakeholders
• The principles of good data visualization design

Module 5: Introduction to Machine Learning

• The fundamental types of machine learning (supervised vs. unsupervised)
• Understanding common algorithms (e.g., regression, classification)
• The difference between training and testing data
• The concept of model accuracy and performance
• The role of a PM in an ML project

Module 6: Data-Driven Project Planning

• Using data to define project scope and requirements
• Forecasting project timelines with historical data
• Budgeting and resource allocation using data insights
• The importance of a data strategy in the project plan
• Creating a data-centric project roadmap

Module 7: Risk Management with Data

• Identifying potential project risks from data
• Using predictive models to forecast issues
• Monitoring project health in real-time
• The role of data in proactive risk mitigation
• Case studies in data-driven risk management

Module 8: Performance Measurement and KPIs

• Defining key performance indicators (KPIs) with data
• Measuring project progress and team performance
• The importance of a data-driven feedback loop
• Using dashboards to monitor KPIs
• The difference between leading and lagging indicators

Module 9: Agile and Data Science

• The intersection of Agile methodologies and data science
• The iterative nature of data projects
• Using data to inform sprint planning and retrospectives
• The role of the PM in a data-focused Agile team
• Continuous delivery in a data-driven environment

Module 10: Tools and Technology

• An overview of common data science tools (e.g., Python, R)
• Introduction to data visualization tools (e.g., Tableau, Power BI)
• The use of cloud platforms for data projects (e.g., AWS, GCP)
• Collaborative tools for data teams
• Understanding the technology stack of a data project

Module 11: Business Analytics for PMs

• Using data to analyze business processes
• The importance of business value metrics
• A/B testing and experimentation
• The role of the PM in creating a data-driven culture
• Translating data insights into business actions

Module 12: Communication and Team Collaboration

• Communicating data insights to non-technical stakeholders
• Fostering a collaborative environment between PMs and data teams
• Overcoming communication barriers
• The importance of a shared vocabulary
• Techniques for effective data-focused meetings

Module 13: Ethics in Data-Driven Projects

• The ethical responsibilities of a data-focused PM
• Understanding bias in data and its impact
• Data privacy and security regulations
• The importance of transparency and explainability in AI
• Building a framework for responsible data use

Module 14: Case Studies and Practical Application

• Analyzing real-world data science projects
• Hands-on exercises with sample datasets
• Building a simple project plan for a data initiative
• Presenting data-driven insights to peers
• Applying course concepts to a simulated project

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 10 working days before commencement of the training.