Hands-on AI Courses you won’t find anywhere else, tailored for Product Managers

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AI Mastery for Product Managers

Course Overview

The AI Mastery for Product Managers course is designed for Product Managers who have completed the AI Essentials for Product Managers course and are ready to explore more advanced AI applications.
 

This advanced course teaches product managers to strategically integrate multiple AI technologies. Through hands-on practice, participants learn to combine strategic planning, NLP, generative AI, and ethics frameworks to create comprehensive solutions for complex product challenges. The focus is on leveraging the synergies between tools to drive innovation and lead sophisticated AI initiatives.


The course features a blend of 20-30% theory and 70-80% practical exercises, ensuring that participants gain actionable knowledge to apply immediately in real-world scenarios.

Learning Objectives

  • Understand core AI concepts and their applications in product management.
  • Gain practical experience with affordable AI tools.
  • Make data-driven decisions using AI to optimize product workflows.

Benefits

Elevate your product management with advanced AI skills. Tailored for Product Managers who have completed AI Essentials, this course empowers you to lead complex AI initiatives and drive innovation, focusing on practical application and ethical considerations. By taking this course, you will gain:  

  • Mastery of advanced AI tools and techniques specific to product management
  • Enhanced ability to lead complex AI-driven initiatives within organizations
  • Practical knowledge of measuring ROI for AI initiatives in product management
  • Improved decision-making skills using advanced AI-driven insights
  • Understanding of AI ethics and responsible AI use in product management

What to expect

This course is delivered through our exclusive e-learning platform and includes instructional videos, articles, live demonstrations, quizzes, real-world scenarios, and actionable takeaways. 

  1. Videos and Articles: Each module includes a mix of instructional videos and articles to help you grasp AI concepts and tools.
  2. Advanced Action Plans: Provide an advanced action plan summarizing steps learners can take to apply the module’s content to their strategic AI initiatives.
  3. Scenario-Based Learning: Each module includes scenarios where learners must solve advanced product management challenges using AI tools.
  4. Challenging Quizzes: Each module concludes with a quiz that tests understanding of advanced AI applications.
  5. Reflection Prompts: Encourage learners to think critically about how they will apply advanced AI strategies in their day-to-day product management activities.
  6. Advanced Readings: Provide links to research papers, in-depth tool guides, and additional case studies for learners seeking deeper exploration.

Prerequisites

  1. To enroll in this course, participants must have either completed the AI Essentials for Product Managers course or have significant hands-on experience with the AI tools covered in that program. 
  2. While deep technical skills are not required, a strong level of tech-savviness is essential to fully engage with the advanced AI tools and concepts presented in this course. 

Course Duration

This course takes approximately 25-27 hours to complete, including interactive exercises and hands-on workshops for practical application.

Completion Recognition

Upon completing this course, you will receive a Certificate of Attendance from Next Frontiers AI Academy.

Modules, Learning Objectives and Tools Features

Description: Master advanced AI applications for product discovery using ChatGPT, Amplitude, MonkeyLearn, and Airtable. Learn to conduct comprehensive market research, analyze competitors, and develop features through practical exercises combining multiple AI tools strategically. 


Average Completion Time Estimate: 3 hours


Learning Objectives:

  • Utilize AI tools for advanced market research and trend analysis.
  • Apply AI techniques to gain deep competitor intelligence.
  • Leverage AI for complex feature ideation and prioritization.
  • Create integrated workflows combining multiple AI tools.


Tools Featured:

  • ChatGPT: For market research, competitor analysis, and feature ideation.
  • Amplitude: For user behavior analysis and market trends.
  • MonkeyLearn: For sentiment analysis of competitor content and social media.
  • Airtable: For organizing and tracking competitor information. 


Key Takeaways:

  • How to create sophisticated, multi-tool workflows for product discovery.
  • Techniques for combining AI tools to validate and cross-reference findings.
  • Strategies for automated market and competitor intelligence gathering.

  

Description: Create data-driven product strategies using ProductPlan/Aha!, VWO, and Tableau. Build dynamic roadmaps, validate decisions through advanced A/B testing, and develop compelling data visualizations for stakeholder communication. .


Average Completion Time Estimate: 3 hours and 30 minutes 


Learning Objectives:

  • Develop AI-enhanced product roadmaps that adapt to real-time data.
  • Design and implement advanced A/B testing strategies for strategic validation.
  • Create data visualization systems for tracking roadmap progress.
  • Integrate multiple data sources into strategic planning processes.


Tools Featured:

  • ProductPlan & Aha!: AI-powered roadmapping and strategy development.
  • VWO: Advanced A/B testing for roadmap decisions.
  • Tableau: Visualizing roadmap data.

  

Key Takeaways:

  • How to create adaptive, data-driven product strategies.
  • Techniques for validating strategic decisions through advanced testing.
  • Methods for effective strategic communication through data visualization.

Description:  Apply advanced NLP techniques using MonkeyLearn and Intercom's Resolution Bot. Learn to analyze user feedback, implement sophisticated topic modeling, and create intelligent automated support systems through hands-on practice.


Average Completion Time Estimate: 3 hours


Learning Objectives:

  • Master advanced NLP techniques for comprehensive feedback analysis.
  • Implement sophisticated topic modelling and trend identification.
  • Design intelligent automated support systems using NLP.
  • Create integrated feedback analysis workflows.


Tools Featured:

  • MonkeyLearn: Sentiment analysis and topic modelling.
  • Intercom’s Resolution Bot:  Sophisticated automated customer support interactions.


Key Takeaways:

  • How to extract deeper insights from unstructured feedback
  • Techniques for creating intelligent automated support systems
  • Methods for identifying emerging patterns in user communication.

Description:  Master testing and optimization with VWO, Amplitude, and GrowthBook. Design sophisticated testing strategies, conduct advanced cohort analysis, and implement feature flagging for controlled rollouts through practical exercises.


Average Completion Time Estimate: 3 hours and 30 minutes


Learning Objectives:

  • Design and implement advanced multivariate testing strategies.
  • Master cohort analysis for sophisticated user behavior insights.
  • Create comprehensive feature flagging and rollout strategies.
  • Build integrated testing frameworks across multiple tools.


Tools Featured:

  • VWO: A/B test setup and result analysis.
  • Amplitude: Cohort analysis for user behavior trends.
  • GrowthBook: Feature flagging and testing for optimization.

  

Key Takeaways:

  • How to design and implement sophisticated testing strategies.
  • Techniques for extracting insights from complex cohort analyses.
  • Methods for controlled feature rollouts and risk mitigation.

 Description:  Learn advanced competitive intelligence techniques using ChatGPT, MonkeyLearn, and Amplitude. Create automated research workflows, analyze market trends, and build comprehensive competitive monitoring systems through hands-on practice. .


Average Completion Time Estimate: 3 hours


Learning Objectives:

  • Implement automated competitive intelligence gathering systems.
  • Create sophisticated market analysis frameworks.
  • Design continuous competitor monitoring workflows.
  • Build integrated market insights dashboards.


Tools Featured:

  • ChatGPT: Advanced competitive research and market trend analysis 
  • MonkeyLearn: Competitor sentiment analysis and content classification 
  • Amplitude:Competitive benchmarking and market positioning analysis.


  Key Takeaways:

  • How to build automated competitive intelligence systems.
  • Techniques for continuous market monitoring.
  • Methods for extracting actionable competitive insights.

Description:  Measure AI implementation impact using Google Analytics, Heap, and Tableau. Create sophisticated tracking systems, build ROI frameworks, and develop executive-level dashboards through practical exercises. .


Average Completion Time Estimate: 3 hours and 30 minutes 


Learning Objectives:

  • Design comprehensive AI ROI measurement frameworks.
  • Create advanced tracking systems for AI implementations.
  • Build executive-level dashboards for AI impact visualization.
  • Develop sophisticated success metrics for AI initiatives.


Tools Featured:

  • Google Analytics & Heap: Tracking metrics for AI improvements.
  • Tableau: Building dashboards to visualize ROI.


  Key Takeaways:

  • How to build comprehensive AI measurement frameworks.
  • Techniques for quantifying both direct and indirect AI impact.
  • Methods for communicating AI success to stakeholders.

Description:  Implement ethical AI practices using What-If Tool, OneTrust, and TrustArc. Learn to detect bias, ensure privacy compliance, and create accountability systems through hands-on exercises with real-world applications. .


Average Completion Time Estimate: 3 hours and 30 minutes


Learning Objectives:

  • Implement practical bias detection and mitigation strategies.
  • Create privacy-first AI implementation frameworks.
  • Design compliance systems for AI products.
  • Build ethical decision-making processes for AI initiatives.


Tools Featured:

  • What-If Tool: Advanced bias detection and model behavior analysis.
  • OneTrust: Privacy program management and consent orchestration.
  • TrustArc: Automated privacy compliance assessment and monitoring .


Key Takeaways:

  • How to implement practical ethical AI systems.
  • Techniques for comprehensive privacy management.
  • Methods for ensuring ongoing compliance and accountability.
  • Strategies for integrating multiple compliance tools effectively.

Description:  Build advanced discovery and recommendation systems using Amplitude, Segment, and Optimizely. Create data-driven content discovery experiences, implement personalized recommendations, and optimize through sophisticated testing. 


Average Completion Time Estimate: 3 hours and 15 minutes


Learning Objectives:

  • Build sophisticated content discovery systems.
  • Implement personalized recommendation engines.
  • Design advanced A/B testing frameworks for discovery optimization.
  • Create self-improving recommendation systems.


Tools Featured:

  • Amplitude: User behavior analysis and content interaction tracking.
  • Segment: User data integration and behavioral segmentation.
  • Optimizely:Advanced experimentation for discovery optimization .


Key Takeaways:

  • How to build data-driven discovery systems.
  • Techniques for personalizing content recommendations.
  • Methods for continuous discovery optimization.
  • Strategies for measuring discovery effectiveness.

Check out more courses and workshops to boost your skills!

AI Essentials for Product Managers

The AI Essentials for Product Managers course is designed to provide Product Managers with the foundational knowledge and hands-on experience needed to integrate AI tools into their daily workflows.


The focus is on practical applications of affordable AI tools to enhance decision-making, streamline processes, and improve user experiences.
 

This course emphasizes hands-on learning, with 70% practical exercises and 30% theory, ensuring participants can immediately apply what they learn.


AI Essentials for Product Managers  is a prerequisite for the AI Mastery for Product Managers course.

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