Google ML Engineer Guided Course

This guided course is for learners who want a structured path through Professional Machine Learning Engineer. Start with ordered lessons, answer exam-style questions, review explanations, and use Practice Mode afterward to test retention.

• Follow an ordered Google ML Engineer course path instead of starting with random questions.
• Use source-backed scenarios to connect concepts to practical administration decisions.
• Review why the correct answer fits and why the distractors do not.
• Track course progress on this device and return to the next lesson later.
• Move from guided learning into Practice Mode when you are ready to check retention and speed.

The full course continues in order. These early lessons are crawlable here so you can see the shape of the path before the interactive course loads.

1. Lesson 1: Recognizing ML-Suitable Problems
   Lesson 1 uses Recognizing ML-Suitable Problems to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.1).
2. Lesson 3: Reinforcement Learning Framing
   Lesson 3 uses Reinforcement Learning Framing to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.1).
3. Lesson 5: Custom Vertex AI Workflow Design
   Lesson 5 uses Custom Vertex AI Workflow Design to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.5).
4. Lesson 7: ML Problem Suitability Review
   Lesson 7 uses ML Problem Suitability Review to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.6).
5. Lesson 9: Defining a Measurable Prediction Target
   Lesson 9 uses Defining a Measurable Prediction Target to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.2).
6. Lesson 10: Business-Aligned ML Metrics
   Lesson 10 uses Business-Aligned ML Metrics to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.2).
7. Lesson 11: Recall and Threshold Selection
   Lesson 11 uses Recall and Threshold Selection to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.2).
8. Lesson 14: Reusable Feature Management
   Lesson 14 uses Reusable Feature Management to connect Data Engineering with Data Preparation and Feature Management (GPMLE-2.6).
9. Lesson 16: Grounding LLM Responses With Retrieval
   Lesson 16 uses Grounding LLM Responses With Retrieval to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.3).
10. Lesson 17: Sensitive Data Protection Before LLM Input
    Lesson 17 uses Sensitive Data Protection Before LLM Input to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.3).