niangmohamed/gcp-professional-ml-engineer-learning-path

GCP Professional ML Engineer Learning Path

The Professional ML Engineer Learning Path cover the following chapters:

1. Google Cloud Platform Big Data and Machine Learning Fundamentals (On-demand Training)

   1.1 Google Cloud Platform Big Data and Machine Learning Fundamentals

 2. Machine Learning on Google Cloud (On-demand Training)

   2.1 How Google does Machine Learning

   2.2 Launching into Machine Learning

   2.3 Introduction to TensorFlow

   2.4 Feature Engineering

   2.5 Art and Science of Machine Learning

 3. Advanced Machine Learning with TensorFlow on Google Cloud (On-demand Training)

   3.1 End-to-End Machine Learning with TensorFlow on GCP

   3.2 Production Machine Learning Systems

   3.3 Image Understanding with TensorFlow on GCP

   3.4 Sequence Models for Time Series and Natural Language Processing

   3.5 Recommendation Systems with TensorFlow on GCP

 4. MLOps (Machine Learning Operations) Fundamentals (On-demand Training)

   4.1 MLOps (Machine Learning Operations) Fundamentals

 5. ML Pipelines on Google Cloud (On-demand Training)

   5.1 ML Pipelines on Google Cloud

 6. Perform Foundational Data, ML, and AI Tasks in Google Cloud (Qwiklabs Quest)

   6.1 AI Platform: Qwik Start

   6.2 Dataprep: Qwik Start

   6.3 Dataflow: Qwik Start - Templates

   6.3 Dataflow: Qwik Start - Python

   6.4 Dataproc: Qwik Start - Console

   6.4 Dataproc: Qwik Start - Command Line

   6.6 Cloud Natural Language API: Qwik Start

   6.7 Google Cloud Speech API: Qwik Start

   6.8 Video Intelligence: Qwik Start

   6.9 Perform Foundational Data, ML, and AI Tasks in Google Cloud: Challenge Lab

 7. Explore Machine Learning Models with Explainable AI (Qwiklabs Quest)

   7.1 AI Platform: Qwik Start

   7.2 Using the What-If Tool with Image Recognition Models

   7.3 Identifying Bias in Mortgage Data using Cloud AI Platform and the What-if Tool

   7.4 Compare Cloud AI Platform Models using the What-If Tool to Identify Potential Bias

   7.5 Explore Machine Learning Models with Explainable AI: Challenge Lab

 8. Build and Deploy Machine Learning Solutions on Vertex AI (Qwiklabs Quest)

   8.1 Vertex AI: Qwik Start

   8.2 Identify Damaged Car Parts with Vertex AutoML Vision

   8.3 Deploy a BigQuery ML Customer Churn Classifier to Vertex AI for Online Predictions

   8.4 Vertex Pipelines: Qwik Start

   8.5 Building and Deploying Machine Learning Solutions with Vertex AI: Challenge Lab

 9. Professional Machine Learning Engineer Exam Guide (Guides)

   9.1 Professional Machine Learning Engineer Exam Guide

 10. Professional Machine Learning Engineer Exam (Certification)

   10.1 Professional Machine Learning Engineer