AI Product Management Course in Hyderabad
Plan, launch and measure AI-powered products as a product manager
The AI Product Management course teaches you to manage products that use machine learning and generative AI. You start with product management fundamentals: discovery, user research, prioritisation, roadmaps and metrics. You then learn how AI differs from traditional software, including probabilistic outputs, data dependence and the need for continuous evaluation. Technical fluency modules explain machine learning basics, large language models, prompts, retrieval-augmented generation, agents, fine-tuning versus prompting and the build, buy or partner decision. Core modules cover identifying good AI use cases, writing AI product requirements, designing human-in-the-loop experiences, defining success metrics, building evaluation sets and acceptance criteria, working with data and engineering teams, cost and latency trade-offs, responsible AI, privacy and regulation awareness, launch, experimentation and monitoring. The course suits aspiring and working product managers, business analysts, project managers and founders; no programming is required. Classes run in Ameerpet, Hyderabad, and in live online batches, and finish with a capstone product proposal.
Syllabus
Product Management Foundations
- •Product manager role, product lifecycle and team structure
- •Customer discovery, problem statements and value propositions
- •Strategy, vision, roadmaps and prioritisation frameworks
- •Lab: Write a problem statement and a one-page product brief
- •Outcome: Apply core product thinking before adding AI
Product Metrics & Experimentation
- •North star metrics, input metrics and guardrail metrics
- •Funnels, cohorts and retention basics
- •A/B testing fundamentals and interpreting results
- •Lab: Define a metrics tree for a sample product
- •Outcome: Measure product success with the right numbers
AI & Machine Learning Fundamentals for PMs
- •Machine learning in plain language: data, features, models and predictions
- •Classification, regression, recommendation and ranking examples
- •Precision, recall, false positives and the cost of errors
- •Lab: Choose error trade-offs for a fraud detection feature
- •Outcome: Discuss ML trade-offs with data scientists
Generative AI & LLMs for PMs
- •How LLMs work, their strengths and failure modes
- •Prompting, retrieval-augmented generation, tool use and agents at a product level
- •Prompting versus RAG versus fine-tuning; model selection by cost, latency and quality
- •Lab: Prototype a simple assistant with an AI chat tool
- •Outcome: Understand what is feasible and what is risky
Finding & Validating AI Use Cases
- •Where AI adds value and where rules or simple automation suffice
- •Feasibility: data availability, quality, accuracy needs and risk
- •Value estimation and prioritisation of AI opportunities
- •Lab: Score five candidate AI features for value and feasibility
- •Outcome: Pick AI projects that are worth building
AI Product Requirements & UX
- •Writing product requirements for probabilistic features
- •Designing for uncertainty: confidence, explanations, fallbacks and escalation
- •Feedback loops and human-in-the-loop workflows
- •Lab: Write a requirements document for an AI assistant
- •Outcome: Specify AI features engineers can build
Evaluation, Quality & Acceptance Criteria
- •Building evaluation datasets with real examples
- •Rubrics, automatic metrics, LLM-as-judge limits and human review
- •Defining launch criteria and quality gates
- •Lab: Create an evaluation set and rubric for an AI feature
- •Outcome: Decide whether an AI feature is good enough to ship
Data, Teams & Delivery
- •Working with data scientists, ML engineers and designers
- •Data sourcing, labelling, privacy and quality
- •Planning AI delivery: uncertainty, spikes, iteration and MLOps basics
- •Lab: Create a delivery plan with milestones and risks
- •Outcome: Coordinate cross-functional AI delivery
Cost, Latency & Business Models
- •Cost drivers: tokens, compute, data and people
- •Unit economics and pricing models for AI features
- •Build, buy or partner decisions and vendor evaluation
- •Lab: Estimate the unit economics of an AI assistant
- •Outcome: Build a business case for an AI product
Responsible AI, Privacy & Regulation
- •Bias, fairness, safety and transparency
- •Privacy, consent and data protection awareness, including India's data protection law at an overview level
- •Risk assessments, red teaming and governance
- •Lab: Run a risk review on an AI feature
- •Outcome: Reduce harm and legal risk
Launch, Monitoring & Iteration
- •Staged rollouts, beta programmes and expectation setting
- •Monitoring quality, usage and cost after launch
- •Handling AI incidents and iterating on feedback
- •Lab: Plan a launch and monitoring dashboard
- •Outcome: Operate an AI product after release
Capstone & Career Preparation
- •Capstone: complete AI product proposal with PRD, evaluation plan, metrics, risks and roadmap
- •Product case and metrics interview practice
- •Portfolio presentation and feedback
- •Outcome: A portfolio-ready AI product proposal
Tools Covered
Projects Included
- AI Opportunity Assessment: Score five AI use cases for value, feasibility and risk for a chosen industry; deliverable is a ranked assessment with recommendations.
- AI Feature PRD: Write a full product requirements document for an AI assistant including fallbacks and escalation; deliverable is a PRD and mock screens.
- Evaluation Plan: Create an evaluation dataset, rubric and launch criteria for an AI feature; deliverable is a test set and a go or no-go checklist.
- Unit Economics Model: Estimate cost per request and break-even for an AI feature; deliverable is a spreadsheet model with scenarios.
- Capstone AI Product Proposal: Present a complete AI product with strategy, metrics, risks and roadmap; deliverable is a written proposal and a presentation.
Start Your Journey Today
Interested in AI Product Management? Fill in your details and we'll get back to you.
Call: +91 9908099980Prerequisites & Eligibility
Understand the foundation and skills needed to succeed in the AI Product Management course.
Course Prerequisites
- Any graduate is eligible for enrollment across all program tracks
- Dedication to work on real-time scenario projects and live client project implementations
- Willingness to engage in aptitude, soft skills and interview readiness sessions
- Commitment to complete full-day training or intensive/internship program schedules
Why Choose GloryTecks
Build practical capabilities through structured learning, expert mentors and hands-on projects.
5+ Years of Excellence
Established training institute in Hyderabad with a proven track record of producing industry-ready professionals.
Expert Faculty
Learn from trainers with real-world industry experience, who teach the way the work is actually done.
Placement Assistance
A dedicated placement team with tie-ups across hiring companies. We support you until you get hired.
Comprehensive Curriculum
Updated syllabus covering the latest technologies and industry best practices, with hands-on projects.
Career Growth Focus
Not just training, but complete career transformation with soft skills and interview preparation.
Online & Classroom
Attend live online batches or classroom training at our Ameerpet centre, whichever suits you.
Flexible Batches
Weekday, weekend and online batch timings to suit working professionals, students and freshers.
Real-time Projects
Work on real-time scenario projects so you finish with practical experience to show employers.
We provide placement support with direct access to hiring companies, along with comprehensive training that helps freshers become job-ready professionals.
Certification
Explore certification and practical learning opportunities with a focus on AI Product Management.
Certificate of Completion
AI Product Management
This certifies that
[Your Name]
has successfully completed the
AI Product Management
Training Program
GloryTecks
Ameerpet, Hyderabad
Certificate ID
GT-YYYY-XXXX
Certificate Includes
- Course completion certificate from GloryTecks
- Project completion certificates
- Internship completion certificate for eligible internship programs
- Digital certificate with a unique verification ID
- Shareable on LinkedIn and other professional platforms
- Valid proof of skill acquisition for employers
- Includes the detailed syllabus covered
Industry Focus
A certificate built around the tools and skills employers ask for, adding credibility to your resume.
Skill Validation
Proves your expertise in the course and the technologies you worked with.
Career Advancement
Strengthens your profile when you apply for jobs and negotiate your salary.
Digital & Physical
Get a digital certificate for online sharing and a physical copy for framing.
Course Certificate
Upon successful completion of the training program
Project Certificate
For major projects completed during training
Course Features & Highlights
Build a strong foundation through a structured AI Product Management course with practical learning and hands-on exposure.
Live Projects
Work on real-world projects from day one with industry use cases.
Expert Trainers
Learn from industry professionals with real-world experience.
Placement Support
Dedicated placement team with assistance until you get hired.
Industry Certification
Get certified and boost your resume with recognized credentials.
LMS Access
Access to learning materials and recorded sessions.
Mock Interviews
Weekly mock interviews to prepare you for real job scenarios.
Resume Building
Professional resume preparation and LinkedIn profile optimization.
Additional Benefits
- Flexible Payment Plans
- 6-12 Months LMS Access
- Doubt Clearing Sessions
- 24/7 Learning Support
Frequently asked questions
What does the AI Product Management course syllabus cover?
Do I need programming skills to become an AI product manager?
Can freshers join the AI Product Management course?
How is AI product management different from regular product management?
Will I build an AI product myself?
Does the course cover regulation?
How is this different from the Forward Deployed Engineer course?
Which jobs can I target after this course?
How long is the AI Product Management course at GloryTecks, and how many hours a week?
Is the AI Product Management course available as live online training?
What is the fee for the AI Product Management course in Hyderabad?
Will I get a certificate after the AI Product Management course?
What placement support do AI Product Management students get?
Best AI Product Management Training in
Ameerpet, Hyderabad
Located at Ameerpet — Hyderabad’s IT training hub. Easily accessible from all areas of Hyderabad. Just 2 minutes walk from Ameerpet Metro Station.
Placement Support
Career support covers resume and LinkedIn preparation, mock interviews and a portfolio of 5 course projects. Roles that use these skills include Associate Product Manager, Product Analyst, Business Analyst (AI), Technical Program Manager (entry level); support is guidance with the job search, not a guarantee of a job.