AI for Data & Product: Analytics, Strategy & Decisions

Explore data analysis fundamentals and its role in finance, healthcare, and business decisions, and learn to turn data into actionable insights using statistical analysis, data visualization, Excel, SQL, and Python.

Learn data collection and acquisition foundations, from surveys to web scraping and sensors. Distinguish internal from external sources using automation tools like Python and extract, transform, and load processes.

Refine and transform raw data to ensure accuracy and reliability, using techniques like imputation, outlier detection and handling, normalization, aggregation, and encoding with tools such as Excel, Python, and R.

Explore how exploratory data analysis reveals patterns, outliers, and trends through descriptive statistics and visualizations, including histograms, box plots, and scatter plots, guiding data preparation and informed modeling decisions.

Explore inferential statistics to test hypotheses, quantify uncertainty with confidence intervals, and model relationships using correlation, regression, anova, and chi-square to drive data-driven decisions.

Data visualization transforms raw data into graphical representations that reveal patterns, trends, and insights for clear, actionable decision making. Design dashboards and visuals with key metrics for quick, audience-specific insights.

Use predictive analytics to leverage historical data and machine learning to build models that forecast future outcomes, evaluate accuracy, precision, and recall, and guide proactive decisions.

Translate data analysis into clear, actionable business insights and recommendations that inform strategy, using well-structured reports and visuals for non-technical stakeholders.

Explore data privacy and ethics, including GDPR and CCPA, consent, and data minimization. Implement encryption, access controls, anonymization, and audits to protect individuals and build trust in data-driven work.

Explore essential tools for data analysis, including Excel's pivot tables and charts, SQL, Python, and R, and leverage cloud solutions like Google BigQuery and AWS Redshift for scalable insights.

Build a professional data analyst portfolio with diverse projects in data cleaning, analysis, visualization, and modeling, documenting the process using Excel, SQL, Python or R, and Tableau.

Explore data analyst career paths, market trends, and growth opportunities across finance, healthcare, retail, marketing, and tech, while refining resumes and interview prep with SQL, Python, R, and data visualization.

Identify and clean missing values in an Excel dataset, replace them with the average, analyze regional sales with sumifs, and build pivot tables to summarize by region and product.

Finish the professional data analyst program and build foundational data analysis skills, while pursuing continuing education, certifications, and available resources for ongoing growth.

Explore ai prompt engineering as the art of communicating with ai models to optimize ideation, analysis, creation, and feedback, while understanding limits like hallucination, bias, and outdated knowledge.

Learn how AI-powered data and ChatGPT apply to product management and innovation, guided by Alex, head of the School of Business and Management at MTF.

Supercharge product management with ai by using ChatGPT for brainstorming, market understanding, documentation, and marketing, and apply practical techniques, real world examples, ethics and best practices to build better products.

Understand chatgpt as a powerful language model for text generation and conversation, and learn to craft effective prompts with context and clarity for product tasks like user stories.

Explore how AI-powered data and product masterclass reveals how AI and ChatGPT reshape product management through automation and augmentation, guiding ideation, planning, development, launch, and iteration with data privacy.

Learn to craft effective prompts for product management with ChatGPT, guiding objective, output format, audience, and necessary background, using six blocks—task, context, role, requirements, boundaries, reasoning—and iterative refinement.

Leverage ChatGPT to speed up competitive analysis through prompt engineering, analyzing reviews at scale, and identifying market gaps and emerging trends, with practical prompts and templates.

Use ChatGPT to build user personas from data and uncover needs and pain points. Analyze social media conversations and open-ended feedback to inform product decisions and craft effective surveys.

Identify new market opportunities by analyzing trends and adjacent markets, uncover unmet needs, and use ChatGPT to brainstorm product concepts, features, and business models like subscriptions, freemium, and transactional.

Learn to craft effective prompts for ChatGPT by defining objectives, audience, and context, and using task descriptions, roles, and boundaries to tailor outputs for competitor analysis.

Brainstorm and generate product ideas with ChatGPT as a collaborative partner, exploring variations, design options, pricing models, and marketing approaches while learning structured prompt techniques to overcome creative blocks.

Develop and refine product concepts by elaborating ideas into concrete features, user flows, and stories, while exploring technical, market, and revenue considerations with AI-assisted brainstorming.

Brainstorm 20 names and 10 taglines to build a branding layer with the right tone, then test ideas with focus groups and surveys for a meal planning app.

Leverage AI to elicit user requirements by crafting interview guides, analyzing transcripts with thematic and sentiment insights, and generating user stories plus acceptance criteria.

Turn gathered requirements into clear, concise product specifications with ai-assisted drafting, structured templates, and traceable, testable details for software, hardware, or services.

Use ai to automate documentation tasks, with ChatGPT generating concise summaries from reports, drafting facts sections and user guides, and enforcing consistency across project documents.

ChatGPT helps generate potential roadmap options and compare strategic directions such as market entry, product expansion, and diversification, with milestones, dependencies, risk flags, and visual timelines.

Prioritize features and initiatives with a data-driven approach, weighing impact against effort using Moscow, rice, and Kano, and using AI tools like ChatGPT for initial analysis.

learn to communicate a product roadmap effectively by tailoring concise summaries and visuals for executives, stakeholders, and the development team, using ChatGPT to craft audience-specific narratives and messages.

Leverage AI, including ChatGPT, to brainstorm UI layouts and components by describing the screen purpose, target users, and key information to generate diverse, actionable ideas.

Create and refine text-based user flow diagrams with AI by outlining each step, decision point, and goal, using a password reset scenario as a practical draft before diagramming.

Generate user testing scripts and probing questions to test usability, track metrics like time on task and success rate, define success criteria, and use ChatGPT to analyze feedback for insights.

Leverage AI to identify accessibility issues and generate design recommendations, referencing WCAG guidelines to improve alternative texts, color contrast, keyboard navigation, and accessibility for visual, motor, cognitive, and hearing impairments.

Use ai tools to generate initial drafts for website copy, headlines, social posts, and email campaigns; tailor messaging to audience segments with tones and storytelling that emphasize benefits.

Develop comprehensive product launch plans and communication strategies using ChatGPT, outlining pre-launch, launch, and post-launch phases, timelines, milestones, and materials like press releases and teasers.

Analyze marketing performance with ChatGPT to summarize website analytics, social media insights, and email metrics, highlight trends, and generate data-driven optimization ideas for campaigns and A/B tests.

Learn how ChatGPT analyzes structured product data to reveal user behavior patterns and key feature usage. It helps articulate insights and quick narrative summaries while complementing traditional analytics tools.

Interpret your data to identify areas for product improvement and use ChatGPT to analyze feedback, perform sentiment analysis, surface key issues, and generate hypotheses for A/B tests.

Track key product metrics and KPIs to gauge performance against goals, with ChatGPT helping define, categorize, and report on these metrics across acquisition, activation, retention, revenue, and referrals.

Embrace privacy by design to minimize data collection and use encryption, access controls, and anonymisation. Ensure transparency, consent, and clear data retention policies to comply with GDPR, CCPA, and PIPEDA.

Navigate the evolving landscape of intellectual property and copyright for AI generated content, clarifying ownership, terms of service, attribution, and licensing to ensure compliance and originality.

Identify and mitigate bias in AI outputs by diversifying training data, applying fairness metrics, and auditing results to build inclusive, fair, and ethical AI-driven products.

Explore transparency and explainability in AI, focusing on model interpretability and XAI. Learn how to disclose AI use and publish transparency reports to build trust.

Master quality prompts—from basic, to focused, to comprehensive—and iterate on AI outputs. Apply critical thinking to assess data privacy and security, IP and copyright, bias, and transparency in product management.

Learn product development and management from definition to lifecycle optimization, including user-centered design, idea generation, validation, prototyping, testing, and agile implementation.

Explore how product development and management drive innovation through ideation, design, testing, and commercialization, guiding the full product life cycle for business growth in dynamic markets.

Generate and refine product ideas through brainstorming, customer insights, and market trend analysis, then validate concepts with prototypes, user testing, and feasibility assessments.

Design products by aligning user needs with business goals through simplicity, functionality, and aesthetics, using user research, personas, and iterative design to prototype rapidly with paper, wireframes, and 3D printing.

Explore usability testing and user experience evaluation with real users to identify pain points, collect actionable feedback, and validate product usability through in-person and remote tests.

Plan and execute a strategic product launch and commercialization by defining objectives, audiences, messaging, and cross-functional collaboration, then select go-to-market channels, set pricing, design packaging, and run promotional campaigns.

Examine the product lifecycle from introduction to decline to identify stage-specific strategies. Optimize the portfolio with BCG matrix and life cycle analysis to guide resource allocation.

Explore agile product development as a mindset of adaptability, collaboration, and customer centricity that delivers value through iterative work and feedback, while applying principles and practices like Scrum and Lean.

Identify and monitor KPIs and metrics such as customer acquisition costs, customer lifetime value, product adoption rate, and user engagement, and drive data-driven decisions to improve product performance.

Explore real-world product success stories from Apple, Tesla, Netflix, Kindle, and Google, revealing how vision, execution, sustainability, and global expansion drive ecosystem and user experience.

Explore agile foundations, learn user stories, story points, planning poker, and sprints, and apply Kanban, Lean, and XP with tools like Jira and Trello.

Explore scrum as an agile, empirical framework that uses transparency, inspection, and adaptation to deliver small increments, maximize customer satisfaction, and govern product backlog, sprint backlog, and events.

Master PMP methodology by exploring five process groups, ten PMBoK knowledge areas, and tools like CPM, Gantt charts, and earned value management for project success.

Compare agile, scrum and PMP to highlight their similarities in delivering value, collaboration, and risk management, and understand how differences in planning, governance, and roles guide when to use each.

Master data storytelling and communicate insights effectively in the ai-powered data & product masterclass led by Alex, a business school instructor and researcher.

Learn to transform overwhelming data into clear, compelling stories by understanding your audience, defining objectives, and applying ethical implications and visual storytelling to drive better decisions.

Decode the audience context, needs, and potential biases to set a clear objective and channel, then craft ethical data stories with a three minute story, big idea, and storyboard.

Explore gestalt principles—proximity, similarity, closure, continuity, and connection—and design ethical data visualizations that guide attention, reveal relationships, and consider memory and preattentive attributes like color, size, shape, and position.

Choose visuals that amplify your message: text for numbers, line charts for trends, scatter plots for relationships, and bar charts with a zero baseline for comparisons, avoiding misleading pie charts.

Eliminate clutter and non-informative elements to sharpen data visuals. Use contrast, alignment, whitespace, and a clear visual hierarchy to guide the audience and tell a precise data story.

Master guiding your audience’s attention by using preattentive attributes such as color, size, and intensity to highlight key data, build visual hierarchy, and tell a clear data story.

Turn raw data into a compelling data story by weaving plot, twists, emotion, and visuals into a journey with a clear call to action, connecting audiences through shared understanding.

Achieve clear data storytelling by aligning horizontal logic and vertical logic, linking each point to evidence, using reverse storyboarding, and ethically reinforcing insights.

Analyze real world data visualizations to sharpen clarity, storytelling, and ethical practices, avoid irrelevant visuals, and apply fresh perspective strategies like explain it to a child, feedback, and paper sketching.

Master data storytelling in the ai-powered data and product masterclass by decoding context, understanding audience biases, and crafting compelling narratives with visuals that highlight insights and drive action.

Explore how to turn data into impactful stories by focusing on narrative over numbers, illustrated with the Little Red Riding Hood tale to connect with audiences.

Set expectations for how work is evaluated and rewarded in 2026 across roles, seniority levels, and industries, reflecting shifted value creation, with AI impact and a tool-agnostic, credible mindset.

Pause to reflect on what worked and what didn't, and decide what to carry forward in 2026. AI is a baseline; use it responsibly to enhance judgment, decisions, and outcomes.

In 2026, the durable workflow centers on clear problem framing, high quality inputs, and an AI assistant. Human validation and purposeful communication turn insights into meaningful outcomes.

In 2026, professionals are judged by prioritization and outcomes, not volume or activity. They gain advantage through reliability, explainability, and ownership of decisions across roles.

In 2026, AI moves from experimentation to operational use, integrated into daily workflows for analysis, content generation, and decision support, with reliable, repeatable results guided by judgment.

in 2026, work across all roles centers on framing problems before solving and negotiating solutions across teams, with ambiguity normal and explanations clear and concise under time pressure.

Learn to balance speed and responsibility in 2026 by separating low-risk from high-stakes decisions, leveraging AI for safe acceleration while preserving human accountability.

Question AI outputs and apply human judgment in high-stakes decisions to protect trust and compliance. In 2026, treat AI as advice, validate decisions, and explain AI outputs to others.

Frame insights around decisions to deliver meaning, not volume, in 2026. Filter noise, highlight what matters, and provide clear implications to guide choices and risks.

Frame decisions in 2026; tools amplify assumptions. Ask three questions before any task: what decision does this support, what could go wrong, and who owns the outcome.

Distinguish replaceable work from defensible work, and focus on judgment, trust, and domain depth to stay relevant in 2026.

Stay valuable as tools evolve by building durable capabilities, critical thinking, domain expertise, ethical judgment, communication, and learning agility. Focus on human-AI collaboration, enduring judgment, and credibility that builds trust.

Stop unimpactful busy work and focus on what moves outcomes forward, keep habits that create enduring value, and build one habit that strengthens judgment to boost trust across any discipline.