Pass the MLOps Engineer Associate Certification in Just 5 Days
Live instructor-led training, official courseware, hands-on labs, exam vouchers, and a free retake — all in one package.
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MCA MLOps Engineer Associate Certification (AI-300) Boot Camp
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Course Description
- Description
- Prerequisites
- Our Facilities
- Why Choose Us
- Microsoft Gold Learning Partner
- What You'll Learn
Description
Prerequisites
Working knowledge of Python or R programming
Experience developing and training machine learning models
Familiarity with Azure Machine Learning concepts and workflows
Understanding of core generative AI concepts and Azure AI services
Our Facilities
CAREER CAMPS FACILITIES
CAMPUS – Career Camps built out a stand alone training center (not a hotel conference room) with spacious classrooms, new desk, Herman Miller Aeron chairs & comfortable common areas. Each student has a dedicated desk with two monitors. Each classroom has a maximum of two rows – so everyone is able to be engaged without the “back row” feeling.
CLASSROOM EQUIPMENT – Students work on a dedicated Dell Client Desktop with 32GB memory with 512GB SSD drives – All Labs are executed the extremely fast Microsoft Data Center Hosted Lab Environment.
CAMPUS INTERNET – The campus is connected with a 1Gbps (1,000 Mbps) Verizon Fios Business Connection which provides complete internet (including VPN) access for students.
COMMON AREA – Amenities including snacks, drinks (Coffee, 100% juices, sodas, etc) all complimentary.
LODGING – We use the Hyatt Place Lakewood Ranch. This “upgraded” hotel offers extremely comfortable beds, great breakfast and very fast internet access.
NEAR BY AMENITIES – Many shops, restaurants and grocery options are available within walking distance. Additionally – the hotel provided scheduled shuttle services. Restaurants like Bone Fish Grill, Ruby Tuesday’s, Five Guys, Chipotle, Quiznos, Chili’s and over 20 additional choices in the immediate area. All of these options are offered in a pedestrian walking village.
Why Choose Us
CAREER CAMPS DIFFERENCE
Career Camps provides an in-depth hands on learning environment. Our instructors teach using demonstrations and explain concepts beyond the scope of the courseware. The best instructors are contracted from all across the US. These professionals are real world consultants who actually implement these technologies. Career Camps knows our clients work in the “real world” and it only makes sense to have an instructor with the experience in the real world.
Facilities – Many of our competitors over-crowd classrooms by placing 2 to 3 students per desk and 20+ students per instructor. Often these companies “extend” the life of very old equipment with slow performance on the software used today. Our average class size is 8 students. Our facilities have the best equipment with the most comfortable, focused environment for learning.
Instructors – Our CEO, Chester Flake holds one of the rarest Microsoft Certifications – the Microsoft Certified Learning Consultant (MCLC) Certification. This certification reflects a commitment to make sure our instructors are also actively engaged in real world consulting projects. Students expect a professional who can answer questions and demonstrate the technology.
Face to Face Training – We believe the best way to interact and learn is face to face training. Many of our competitors which offer local training are simply providing students with headphones/mic to attend class with an instructor at a remote location.
Test Pass – We offer a free retake voucher (if needed) for each of the exams required for certification. Any training center offering a “100% pass guarantee” would have to use unethical practices or unlimited test vouchers (which is not likely or practical).
Distractions – Students often look for a “local” training center so they can be close to home and work. Boot camp requires a tremendous time commitment during the program. Long class hours combined with self study each evening. The goal of boot camp is to achieve certification in a fraction of the time. We strongly recommend students attend camp away from home and work in a focused, distraction free environment.
Boot Camp – Boot camp is an accelerated training focused on teaching technology and testing students on the official exams. Most training providers “added” boot camps to the existing standard training classes they offer. These training centers think a boot camp is just a regular class where you send the student home with a voucher on the last day. Career Camps administers exams throughout the camp. Equally important – not every trainer can teach a boot camp and not all courseware is designed for boot camp format. Our trainers know the boot camp format and our courseware is designed for accelerated learning.
Florida – Career Camps has one of the most scenic locations boasting some of the best weather in US. We believe students should have a comfortable and inviting atmosphere while attending these otherwise intense programs. We place our location, facilities and amenities up against that any competitor.
Microsoft Gold Learning Partner
What You'll Learn
- Design and run machine learning experiments using Azure Machine Learning, including AutoML and model tracking
- Optimize model performance through hyperparameter tuning and structured experimentation
- Build and automate end-to-end ML workflows using pipelines and CI/CD with GitHub Actions
- Deploy, test, and manage machine learning models in production environments
- Implement MLOps practices to improve reliability, scalability, and repeatability of AI solutions
- Apply GenAIOps principles to develop and manage generative AI applications using Microsoft Foundry
- Manage prompts and AI agents as version-controlled assets using Git-based workflows
- Evaluate and optimize AI models and agents using structured metrics for quality, cost, and performance
- Automate AI evaluation processes to ensure continuous improvement and consistency
- Monitor AI application performance, including latency, usage, and cost
- Analyze and debug AI systems using tracing and observability techniques to improve reliability
Course Outline
Experiment with Azure Machine Learning
- Introduction
- Preprocess data and configure featurization
- Run an automated machine learning experiment
- -Evaluate and compare models
- Configure MLflow for model tracking in notebooks
- Train and track models in notebooks
- Evaluate models with the Responsible AI dashboard
- Exercise: Find the best classification model with Azure Machine Learning
Perform Hyperparameter Tuning with Azure Machine Learning
- Introduction
- Define a search space
- Configure a sampling method
- -Configure early termination
- Use a sweep job for hyperparameter tuning
- Exercise: Run a sweep job
Run Pipelines in Azure Machine Learning
- Introduction
- Create components
- Create a pipeline
- Run a pipeline job
- Exercise: Run a pipeline job
Trigger Azure Machine Learning Jobs with GitHub Actions
- Introduction
- Understand the business problem
- Explore the solution architecture
- Use GitHub Actions for model training
- Exercise
Trigger GitHub Actions with Feature-Based Development
- Introduction
- Understand the business problem
- Explore the solution architecture
- Trigger a workflow
- Exercise
Work with Environments in GitHub Actions
- Introduction
- Understand the business problem
- Explore the solution architecture
- Set up environments
- Exercise
Deploy a Model with GitHub Actions
- Introduction
- Understand the business problem
- Explore the solution architecture
- Model deployment
- Exercise
Plan and Prepare a GenAIOps Solution
- Introduction
- Explore use cases for GenAIOps
- Select the right generative AI model
- Understand the development lifecycle of a language model application
- Explore available tools and frameworks to implement GenAIOps
- Exercise: Compare language models from the model catalog
Manage Prompts for Agents in Microsoft Foundry with GitHub
- Introduction
- Apply version control to prompts
- Understand Microsoft Foundry agents and prompt versioning
- Organize prompts in GitHub repositories
- Develop safe prompt deployment workflows
- Exercise: Develop prompt and agent versions
Evaluate and Optimize AI Agents Through Structured Experiments
- Introduction
- Design evaluation experiments
- Apply Git-based workflows to optimization experiments
- Apply evaluation rubrics for consistent scoring
- Exercise: Evaluate and compare AI agent versions
Automate AI Evaluations with Microsoft Foundry and GitHub Actions
- Introduction
- Understand why automated evaluations matter
- Align evaluators with human criteria
- Create evaluation datasets
- Implement batch evaluations with Python
- Integrate evaluations into GitHub Actions
- Exercise: Set up automated evaluations
Monitor Your Generative AI Application
- Introduction
- Why monitoring matters
- Understand key metrics to monitor
- Explore monitoring with Azure
- Integrate monitoring into your application
- Interpret monitoring results
- Exercise: Enable monitoring for a generative AI application
Analyze and Debug Your Generative AI Application with Tracing
- Introduction
- Why tracing is important
- Identify what to trace in generative AI applications
- Implement tracing in generative AI applications
- Debug complex workflows with advanced tracing patterns
- Analyze trace data to inform decisions
- Exercise: Enable tracing for a generative AI application
Frequently Asked Questions
What is the Microsoft MLOps Engineer Associate (AI-300) Boot Camp?
The Microsoft MLOps Engineer Associate AI-300 Boot Camp is an instructor-led training program designed to prepare professionals for Exam AI-300: Operationalizing Machine Learning and Generative AI Solutions. The training focuses on implementing MLOps and GenAIOps solutions on Microsoft Azure, including machine learning lifecycle management, AI infrastructure, deployment, monitoring, observability, and optimization.
What does the Microsoft AI-300 exam cover?
The AI-300 exam covers five major areas: designing and implementing MLOps infrastructure; implementing machine learning model lifecycle and operations; designing and implementing GenAIOps infrastructure; implementing generative AI quality assurance and observability; and optimizing generative AI systems and model performance.
Who should take the Microsoft MLOps Engineer Associate Boot Camp?
This boot camp is ideal for machine learning engineers, data scientists, AI engineers, DevOps professionals, cloud engineers, and other IT professionals responsible for deploying, managing, automating, or monitoring machine learning and generative AI solutions in Azure environments. Microsoft recommends a background in data science, Python programming, and entry-level DevOps practices.
Do I need prior MLOps or machine learning experience before taking the AI-300 Boot Camp?
Yes. AI-300 is an intermediate-level certification, so some experience with machine learning, Python, and DevOps concepts is recommended. Familiarity with Azure Machine Learning, Microsoft Foundry, GitHub Actions, Azure CLI, and infrastructure-as-code practices can also be beneficial.
What technologies are covered in the AI-300 MLOps training?
The AI-300 certification focuses on technologies and practices including Azure Machine Learning, Microsoft Foundry, GitHub Actions, Azure CLI, Bicep, machine learning lifecycle management, MLOps automation, GenAIOps, AI observability, and generative AI optimization.
What will I learn in an Azure MLOps Engineer Associate Boot Camp?
Participants learn how to design and implement MLOps infrastructure, manage the machine learning model lifecycle, automate machine learning operations, deploy and maintain models, implement GenAIOps infrastructure, monitor AI applications, evaluate generative AI quality, and optimize AI and model performance.
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