kodestree MLOps fundamentals for beginners program starts at the very beginning. What does MLOps mean? Why does it exist? What do people in this field actually do at work? From there, you will steadily build practical skills- using tools that real teams use, completing small hands-on exercises in every module, and finishing with a simple end-to-end project that you built yourself. By the end, you will have the vocabulary, the confidence, and the foundational skills to step into an entry-level ML role or continue with more advanced MLOps training with a solid foundation.
Prerequisites
Since this is a foundation-level program, there are no prerequisites to enroll in this program. But the basics of following make learning more effective and easier.
- Basic Python
Objectives of MLOps Fundamentals
By the end of this program, you will have gone from knowing almost nothing about MLOps to having real, hands-on experience with the foundational tools and workflows that ML teams use every day.
- Understand what MLOps means, why it was created, and how it fits into a company’s AI strategy
- Know the stages of the machine learning lifecycle and what happens at each stage in a real project
- Use Git for basic version control, so your work is tracked and shareable with a team
- Set up and use MLflow to track your experiments and compare different model runs
- Save a trained model in a reusable format and load it back when you need it
- Build a simple API that lets other applications send data to your model and get predictions back
- Create a basic Docker container so your model runs the same way on any machine
- Understand what CI/CD means and see a simple automated workflow in action
- Know what model monitoring is and why it matters once a model is live
- Complete a capstone project that ties every skill together into one working workflow
What You Will Learn
In this program, you will learn the following to build your foundations.
- Understand the fundamentals of MLOps and its role in the machine learning lifecycle.
- Learn how to bridge the gap between data science, machine learning, and DevOps teams.
- Explore the end-to-end machine learning workflow from data preparation to deployment.
- Understand model versioning, experiment tracking, and reproducibility best practices.
- Learn how to automate machine learning pipelines for faster and more reliable model delivery.
- Gain knowledge of Continuous Integration and Continuous Deployment (CI/CD) for machine learning projects.
- Understand data management, data validation, and feature engineering workflows.
- Learn model training, evaluation, testing, and performance monitoring techniques.
- Explore containerization concepts using Docker and orchestration fundamentals with Kubernetes.
- Understand model serving, deployment strategies, and production-ready ML systems.
- Learn how to monitor model performance, detect drift, and manage model retraining.
- Gain insights into cloud-based MLOps platforms and infrastructure management.
- Understand security, governance, compliance, and scalability considerations in MLOps.
- Explore popular MLOps tools and frameworks used in the industry.
- Build a strong foundation for advanced MLOps, Machine Learning Engineering, and AI Operations roles.
Who is this Program For?
This fundamentals program is for anyone starting from scratch who wants to understand how machine learning works in real companies – not just in textbooks.
- College students in computer science, IT, or data science who want practical, job-relevant skills
- Fresh graduates who have learned Python or ML basics and want to know what comes next
- Working professionals in non-ML roles who want to understand and move into the AI/ML space
- Self-taught developers who can write Python but have never worked on a real ML project
- Anyone who is learning through ML tutorial but wants structured, guided training with a certificate
- People who applied for ML roles and realized they lacked the operational and deployment side of knowledge
- Absolute beginners to MLOps who want a clear, honest starting point with zero assumed knowledge
Tools and Technologies Covered
Every tool in this program is free, widely used in the industry, and taught completely from scratch – no prior installation or setup experience is assumed.
- Python 3 – the primary language for all scripts, exercises, and the capstone project
- Jupyter Notebook – for exploratory coding and hands-on practice in an interactive environment
- scikit-learn – used throughout labs to train simple, easy-to-understand ML models
- Git & GitHub – version control for code and collaboration, taught from the very first command
- MLflow – experiment tracking and model registry, set up and used locally on your own machine
- Flask – building a simple prediction API that your model can serve results through
- Docker Desktop – creating your first container to make your model portable (basics only)
- GitHub Actions – setting up a simple automated workflow that runs when you push code
- VS Code – recommended code editor with beginner-friendly setup guidance provided
Career Outcomes
This MLOps fundamentals program gives you the foundation to pursue entry-level roles where MLOps skills are valued, or to continue confidently into intermediate training for more senior positions.
- Junior MLOps Engineer
- Entry-Level Machine Learning Engineer
- Data Science Intern or Associate
- ML Operations Analyst
- Software Developer (AI/ML focus)
- Technical Support Engineer (ML Tools)
- AI/ML Trainee Programs
Why Choose kodestree for This Program?
- Genuinely zero-to-beginner curriculum
- Every concept is explained with a real-world example before any tool is introduced
- Hands-on lab in every single module
- Live instructor-led classes with actual Q&A, not just recorded videos
- Weekend and weekday batch options to fit around college or work schedules
- Small class sizes – instructors know your name and your progress
- Dedicated doubt-clearing sessions between every class
- Career support with MLOPs interview questions and answers for beginners
- Lifetime access to all recordings and materials, including future updates
- kodestree completion certificate valued by hiring managers across India
