Google Certified Professional Machine Learning Engineer


Grasp ML Algorithms, Knowledge Modeling, TensorFlow & Google Cloud AI/ML Providers. 137 Questions, Solutions with Explanations

Why take this course?

🌟 Grasp Google Licensed Skilled Machine Studying Engineer 🌟

Are you able to unlock the total potential of machine studying and synthetic intelligence on Google Cloud AI/ML Providers? Dive deep into the world of ML algorithms, knowledge modeling, and TensorFlow with our complete on-line course crafted for professionals such as you who aspire to change into Google Licensed Skilled Machine Studying Engineers.

Course Overview:

This isn’t simply one other machine studying course; it’s a transformative journey that may equip you with the talents to translate real-world enterprise challenges into impactful ML use instances. You’ll be taught to strategically select between ML and non-ML options, customized or pre-packaged choices, and outline how your mannequin outputs can remedy complicated issues.

Key Takeaways:

  • Enterprise Problem Translation: Flip enterprise points into ML alternatives with precision.
  • Optimum Resolution Choice: Know when to use ML and which options are most fitted for the duty at hand.
  • Knowledge Modeling Mastery: Perceive and execute knowledge modeling methods successfully.
  • TensorFlow Experience: Achieve hands-on expertise with TensorFlow, Google’s versatile machine studying library.
  • Google Cloud Platform Proficiency: Leverage Google Cloud AI/ML providers for real-world purposes.
  • Complete Query and Reply Financial institution: 137 detailed questions with solutions and explanations to bolster your studying.

Course Highlights:

Module 1: Translating Enterprise Challenges into ML Use Circumstances

  • Determine and articulate how machine studying can handle enterprise challenges.
  • Be taught to border issues in a method that aligns with ML capabilities.

Module 2: Resolution Technique and Downside Definition

  • Grasp the artwork of selecting between ML vs non-ML options.
  • Outline customized ML issues, outcomes of predictions, and enter/output codecs.

Module 3: Knowledge Sources Identification and Enterprise Success Standards Alignment

  • Uncover the place to seek out knowledge to your ML tasks.
  • Set clear success standards based mostly on ML metrics and key outcomes.

Module 4: Danger Evaluation and Dependable ML Resolution Design

  • Perceive the dangers concerned with ML options and the right way to mitigate them.
  • Design scalable, dependable, and out there ML architectures.

Module 5: Selecting Applicable ML Providers and Parts

  • Be taught to pick out the right combination of Google Cloud AI/ML providers to your challenge’s wants.

Module 6: Knowledge Exploration, Evaluation, and Function Engineering

  • Achieve insights into knowledge visualization, statistical fundamentals, and knowledge high quality evaluation.
  • Construct strong knowledge pipelines and deal with lacking knowledge successfully.

Module 7: Mannequin Constructing and Coaching

  • Dive into characteristic creation and preprocessing, making certain consistency and integrity.
  • Be taught greatest practices for mannequin choice and coaching utilizing Google Cloud platforms.

Module 8: Mannequin Testing, Scaling, and Implementation

  • Perceive the right way to take a look at fashions rigorously, together with unit checks and efficiency comparisons.
  • Scale mannequin coaching and serving, each in distributed environments and as a prediction service.

Module 9: Coaching and Serving Pipelines

  • Design and implement complete coaching pipelines with TFX parts.
  • Implement serving pipelines to fulfill particular efficiency targets.

Module 10: Metadata Monitoring, Auditing, and Compliance

  • Grasp experiment monitoring, dataset and mannequin versioning, and lineage understanding.

Module 11: Monitoring, Troubleshooting, and Efficiency Tuning

  • Be taught to watch ML options successfully and troubleshoot points that come up.
  • Optimize coaching and serving for manufacturing environments, using simplification methods as wanted.

Why Select This Course?

This course is meticulously designed to cowl all facets of turning into a Google Licensed Skilled Machine Studying Engineer. With real-world eventualities, hands-on tasks, and a sturdy Q&A piece, you’ll be well-prepared to sort out any ML problem. Plus, with the steerage of our knowledgeable teacher, Deepak Dubey, you possibly can confidently pursue your certification and elevate your profession in AI/ML.

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