Grokking AI for Engineering & Product Managers sounds like a pretty intimidating course.
But actually it’s not.
And as tech products continue to be infused with AI, the higher demand there will be for understanding it.
“What is artificial intelligence (AI)?”
Artificial Intelligence (AI) is the ability of a computer to perform tasks that typically require human intelligence.
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“So what is this AI course all about anyway?”
Grokking AI for Engineering and Product Managers was actually made for engineering and product managers with no experience in AI.
The course shows you:
🔷 the basics of AI
🔷 ethical AI
🔷 rules, practices, and infrastructure
🔷 AI’s connection to machine learning
🔷 algorithms you should be familiar with as an engineering manager or product manager
And many more topics relevant to tech managers.
Understanding AI as a engineering or product manager can help you:
- communicate with diverse teams
- keep projects on task
- solve technical issues
- build trust
Want to know more about the Grokking series on Educative.io?
Check out our full review list.
Grokking AI for Engineering & Product Managers
⚠️ Level: Beginner
|46 Lessons||3 Quizzes||111 Illustrations|
Estimated completion time: 5 hours
The course is broken down into 5 modules:
- AI in Practice
- Real Case Studies
- Responsible AI
- What’s Next
Let’s take a peek at each section.
✨ Module 1: Fundamentals
… what if we want to use computers not just to fetch and display data, but to actually make decisions about data? … What if we want machines to perform cognitive functions we associate with human minds, like perceiving, reasoning, learning, interacting with the environment, problem-solving, and even exercising creativity?– Samia Khalid, instructor of Grokking AI for Engineering and Product Managers
Here is where you’ll learn the absolute basics of AI for engineering and product managers. Topics covered include:
✅ Basics of AI – relationship between artificial intelligence, machine learning and deep learning
✅ Highs and Lows of AI – artificial intelligence throughout history
✅ Understanding Machine Learning – main components, applications
✅ Supervised Learning – algorithms: decision trees, random forests, artificial neural networks (ANN)
✅ Unsupervised Learning – clustering, dimensionality reduction
✅ Deep Learning – activation functions, neural network architecture and types
✅ Natural Language Processing – BERT, word embeddings, one-hot encoding, Word2Vec
✅ Recommendation Systems – building blocks, algorithms, architecture, metrics
✅ Evaluation Metrics – RMSE, precision, recall and confusion matrix, AUC-ROC curve
Each topic is detailed enough to give you a general grasp on AI fundamentals.
✨ Module 2: AI in Practice
People need to trust AI in order to use it. From self-driving cars to Alexa commands, they want to know they’re in good hands.
🚨 Alert: You’re going to see a LOT of jargon in these upcoming lessons. But don’t worry – the instructor explains all of these terms!
✅ Creating Great AI Products – best practices, ML pipeline, feature engineering, optimized refinement, etc.
✅ AI Infrastructure – MLaaS, frameworks (scikit-learn, TensorFlow, PyTorch, Keras), cloud services for AI solutions
✨ Module 3: Real Case Studies
Examining case studies helps you fuse your knowledge with the real world.
So here you’ll look at case studies of high-profile companies:
✅ Starbucks: Millions of AI Infused Cups of Coffee
✅ Netflix: Using AI to Give us Better Entertainment
✅ American Express: AI and Credit Cards
✅ AI for Wildlife Conservation: background, PAWS, Air Shepherd
And from there, you’ll take a machine learning (ML) quiz.
✨ Grokking AI for Engineering & Product Managers Module 4: Responsible AI
This section considers the ethical ramifications of AI. As they say, “with great power comes great responsibility.”
Responsible AI practices include:
✅ Fairness – creating AI apps that treat all people fairly
✅ Interpretability – keeping AI systems understandable
✅ Privacy – AI systems respecting privacy, collection and handling of data, ethical boundaries in data processing
✅ Security – adversarial training (fooling the system), recommended practices
Then you’ll go over 6 fictional case studies of AI issues and ethics.
✨ Grokking AI for Engineering & Product Managers Module 5: What’s Next
The course concludes by examining the state of AI:
✅ The Current State of AI in Numbers – conferences, technical performance, economy, education, autonomous systems, public perception, societal considerations, etc.
✅ Future of AI – work, human experience, data, connectivity and cognitive AI
And from there, you’re provided with recommended resources to take learning AI to the next level.
💰 Grokking AI for Engineering & Product Managers Cost
You can buy this course for $79.
But with all the other deep and machine learning courses on Educative.io, it might be worth getting a subscription:
|Grokking AI for Engineering & Product Managers||Monthly|
|$199 per year|
|Early access to|
Is Grokking AI for Engineering & Product Managers worth it? Conclusion
If you’re an engineering manager or product manager looking for a beginner course for an introduction to AI, Grokking AI for Engineering & Product Managers is worth it.
By introducing concepts in a digestible and relatable manner, it’s easy to follow along. And it makes the learning process energetic instead of tedious.
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