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: ML Problem Suitability Overview
   Lesson 1 uses ML Problem Suitability Overview to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.1).
2. Lesson 2: ML Problem Suitability Application
   Lesson 2 uses ML Problem Suitability Application to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.1).
3. Lesson 3: Reinforcement Learning Overview
   Lesson 3 uses Reinforcement Learning Overview to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.1).
4. Lesson 4: Recognizing ML-Suitable Problems
   Lesson 4 uses Recognizing ML-Suitable Problems to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.1).
5. Lesson 5: ML Problem Suitability Data
   Lesson 5 uses ML Problem Suitability Data to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.1).
6. Lesson 6: Reinforcement Learning Recognition
   Lesson 6 uses Reinforcement Learning Recognition to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.1).
7. Lesson 7: Measurable Prediction Target Overview
   Lesson 7 uses Measurable Prediction Target Overview to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.2).
8. Lesson 8: Aligning Offline Metrics With Business Outcomes
   Lesson 8 uses Aligning Offline Metrics With Business Outcomes to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.2).
9. Lesson 9: Imbalanced Classification Design
   Lesson 9 uses Imbalanced Classification Design to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.2).
10. Lesson 10: Defining a Measurable Prediction Target
    Lesson 10 uses Defining a Measurable Prediction Target to connect Defining the Problem with Problem Framing and Use Case Selection (GPMLE-1.2).