What will you learn in Grokking AI for Engineering & Product Managers Course
Core AI & ML fundamentals: Explore supervised, unsupervised, reinforcement learning, deep learning (CNNs/RNNs), NLP, transfer learning, and evaluation metrics.
Building trustable AI products: Understand AI infrastructure, ethical principles, bias management, and best practices to design reliable, user-centric AI solutions.
Real-world use-case insight: Learn through case studies on Starbucks, Netflix, American Express, and wildlife conservation how AI drives real business value.
Responsible AI & ethics knowledge: Dive into policies, frameworks, and ethical AI decision-making strategies.
Program Overview
Module 1: The Fundamentals
⏳ ~2 hours
Topics: AI, ML, DL architectures, CNN/RNN basics, NLP concepts, transfer learning.
Hands-on: Quizzes following deep dives into these foundational topics.
Module 2: AI in Practice
⏳ ~1 hour
Topics: Trustworthy AI, ML infrastructure, cloud and framework overviews.
Hands-on: Quiz-based scenarios on infrastructure and ethical best practices.
Module 3: Real Case Studies
⏳ ~45 minutes
Topics: Starbucks personalization, Netflix recommendations, AmEx fraud systems, wildlife conservation AI.
Hands-on: Assess case study takeaways through interactive quizzes.
Module 4: Responsible AI
⏳ ~45 minutes
Topics: Ethical frameworks, bias detection, regulatory concerns, transparency methods.
Hands-on: Quiz on responsible practices and classroom-style reflection.
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Job Outlook
Bridging tech & leadership: Empowers engineering and product managers to lead AI initiatives with confidence.
Broader relevance: Applies to roles in product development, AI strategy, innovation, data science, and architecture.
High current demand: Provides an edge in managing AI integrations, ethical frameworks, and product roadmapping.
AI-informed leadership skill: Enables better communication with ML teams, ensuring strategic alignment and responsible delivery.
Specification: Grokking AI for Engineering & Product Managers
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