Master MLOps for effective model deployment and scaling.
Build a project portfolio showcasing end-to-end ML expertise.
Become a Certified MLOps Engineer specializing in deployment.
Unlimited 1:1 Mentorship from experts for support and guidance.
Join Thousands of Data Professionals Who Trust ProjectPro to Accelerate Productivity and Learning
Why ProjectPro?
83%
Learners report they are “Significantly More Confident" in Job Interviews.
74%
Learners report that ProjectPro Courses are Equivalent to Gaining Real Industry Expertise.
MLOps Course Benefits
Build a Job-Ready Portfolio
With ProjectPro, you'll tackle enterprise-grade business use cases, creating a project portfolio that demonstrates your expertise to deliver practical solutions.
Unlimited 1:1 Personalised Mentorship
Our unlimited 1:1 mentor sessions are your secret weapon! Connect with industry pros who've been there, done that, and are excited to guide you on troubleshooting projects, career strategy, or interview preparation every step of the way.
Project-Based Course Curriculum
ProjectPro's course curriculum stands out in the world of online learning. Our courses are entirely online and completely project-based that allows you to apply what you learn in real-world scenarios.
Curriculum Updated with New Projects
We partner with industry experts to keep our curriculum updated with new projects released every month to ensure you learn with access to the latest tools and frameworks.
Gain Industry-Equivalent MLOps Certification
Our certification signifies more than just completion; they represents real-world experience gained through hands-on projects with skills and knowledge that employers value.
Cloud Lab Workspace
Our Cloud Lab Workspace provides a ready-to-use environment for running practical projects tailored specifically for your learning needs.
ProjectPro's MLOps Certification is equivalent to real-world industry experience, preparing you for the demands of the industry.
Follow a structured learning path for MLOps designed to fit your schedule, typically spanning 16-24 weeks.
Complete an End-to-End MLOps project that showcases your skills upon submission.
Once your project is submitted, our industry experts will evaluate your performance and provide constructive feedback , setting you up for successful MLOps certification.
Customer Reviews
I come from Northwestern University, which is ranked 9th in the US. Although the high-quality academics at school taught me all the basics I needed, obtaining practical experience was a challenge. This is when I was introduced to ProjectPro, and the fact that I am on my second subscription year only goes to prove that the ROI is satisfactory.
I managed to switch to analytics companies, only because of the relevant practical experience this product served me with. I now work at a leading healthcare startup as a Senior Analytics Consultant.
I am a customer who is not only satisfied with ProjectPro but also mighty impressed by how Dezyre bends over backward to ensure customer satisfaction. I have had a couple of interactions with Binny and each time I was left happy and content. I also had a conversation with their investors, and I was really glad to articulate my appreciation of the product.
They not only have enterprise-grade projects, but also set up 1:1 sessions with seasoned experts in case we get stuck, or are having trouble understanding a certain concept. As the cherry on the icing, there are experts to guide you with resume writing and interview preparation as well, to culminate the whole process of making you job-ready.
Kudos to ProjectPro!
Abhinav Agarwal
Graduate Student at Northwestern University
I come from a background in Marketing and Analytics and when I developed an interest in Machine Learning algorithms, I did multiple in-class courses from reputed institutions though I got good theoretical knowledge, the practical approach, real word application, and deployment knowledge were missing. ProjectPro helped me bridge that gap. ProjectPro has real-time projects that helped me improve my skills. What I liked most is that I get exposure to so many projects, given the work nature I wouldn't have gotten exposure to such a variety of projects and their approaches. It is helping me apply knowledge to other projects too. I highly recommend ProjectPro to everyone who wants to excel in their DataScience career.
Ameeruddin Mohammed
ETL (Abintio) developer at IBM
I am the Director of Data Analytics with over 10+ years of IT experience. I have a background in SQL, Python, and Big Data working with Accenture, IBM, and Infosys. I am looking to enhance my skills in Data Engineering/Science and hoping to find real-world projects fortunately, I came across Project Pro. Project Pro helped me by providing an in-depth explanation of the end-to-end real-world data engineering projects. From data extraction, transformation, and storage up to data visualization. I learned more about Kafka, AWS, NI-FI, and Spark. Thru the help of the knowledge I gained from Project Pro, I was able to do well in the coding exams, interview and helped me land a job at EY. I will recommend every aspiring data professional as well as existing data science/engineer expert to try Project Pro to enhance their knowledge.
Ed Godalle
Director Data Analytics at EY / EY Tech
ProjectPro is an awesome platform that helps me learn much hands-on industrial experience with a step-by-step walkthrough of projects. There are two primary paths to learn: Data Science and Big Data. In each learning path, there are many customized projects with all the details from the beginner to the expert. As a new data science learner, you can just follow these projects to master the important techniques quickly. It is really helpful for both my research and job searching. Hope you can come and join ProjectPro to win a great future for yourself.
Jingwei Li
Graduate Research assistance at Stony Brook University
As a student looking to break into the field of data engineering and data science, one can get really confused as to which path to take. Very few ways to do it are Google, YouTube, etc. I was one of them too, and that's when I came across ProjectPro while watching one of the SQL videos on the E-Learning Bridge YouTube channel. One of the standout features was that it featured real projects on topics I just read about, across different job descriptions at the time. The main issue was the right path to guide us in using these tools and adding to the resume, and that's exactly what ProjectPro got me through. The fact that I can have a reliable route and videos explaining each tool in detail really motivated me to continue with the platform. Another thing we all struggle with is how to really connect with someone if we're stuck somewhere because there are so many solutions. But this has also been solved by experts we can chat with and believe me when I say this they will do whatever it takes to solve your problem even if it takes longer than expected. In my sophomore year of college and getting hands-on exposure to technologies like PySpark, NLP, Kafka, etc, and being able to really apply the theory and work on a project from start to finish really boosted my confidence in general!
Savvy Sahai
Data Science Intern, Capgemini
ProjectPro is a unique platform and helps many people in the industry to solve real-life problems with a step-by-step walkthrough of projects. A platform with some fantastic resources to gain hands-on experience and prepare for job interviews. I would highly recommend this platform to anyone looking to upskill and stay updated with the latest projects and solutions. Overall this platform is awesome and worth the money spent as we get a lot of value out of it and helps soar our career to greater heights.
Anand Kumpatla
Sr Data Scientist @ Doubleslash Software Solutions Pvt Ltd
I think that they are fantastic. I attended Yale and Stanford and have worked at Honeywell,Oracle, and Arthur Andersen(Accenture) in the US. I have taken Big Data and Hadoop,NoSQL, Spark, Hadoop Admin, Hadoop projects. I have been happy with every project. They have really brought me into the forefront of Data Science and Big data. I would recommend this to everyone. It is more than worth the price. After working with them I feel so much more employable for current projects.
Ray han
Tech Leader | Stanford / Yale University
Having worked in the field of Data Science, I wanted to explore how I can implement projects in other domains, So I thought of connecting with ProjectPro. A project that helped me absorb this topic was "Credit Risk Modelling". To understand other domains, it is important to wear a thinking cap and that's where ProjectPro helped me. I also got a chance to talk to experts who have worked on these domains - they helped me by walking through the project. Kudos to the ProjectPro team!
Yes, MLOps requires coding skills, particularly in languages like Python programming, and knowledge of DevOps tools.
What is the salary of MLOps in India?
The average salary for an MLOps professional in India ranges from ₹10 to ₹20 lakhs per annum, depending on experience and location.
Is MLOps better than DevOps?
MLOps is specialized for machine learning workflows, while DevOps is broader. Neither is inherently better; it depends on your focus.
How to start learning MLOps?
Begin with foundational courses in machine learning, then progress to MLOps-specific training. Practical projects and hands-on experience are crucial.
How long does it take to learn MLOps?
It can take 6 months to a year to become proficient in MLOps, depending on prior experience and learning pace.
What are the prerequisites to learn MLOps?
A solid understanding of machine learning, programming skills in Python, and familiarity with DevOps concepts are essential.
How to Learn MLops?
Enroll in comprehensive courses, engage in practical projects, and stay updated with the latest tools and techniques in the MLOps ecosystem.
What kind of audience is the MLOps course intended for?
The MLOps course is designed for a wide range of learners, including data engineers, computer science graduates, software developers, and data science professionals. Whether you're a beginner looking to enter the field or an experienced professional aiming to deepen your knowledge, this course caters to all levels.
What do I need to qualify for the MLOps certification course?
To qualify for the MLOps certification course, a basic understanding of machine learning concepts is recommended. While the course accommodates different experience levels, prior knowledge in areas like exploratory data analysis, programming, or machine learning projects will help you grasp the advanced topics more easily.
What will I learn in this MLOps course?
In this MLOps course, you'll gain a comprehensive understanding of machine learning operations, including building and deploying models, managing them in production, and scaling ML workflows. The course covers everything from foundational ML concepts to advanced techniques for maintaining and automating ML models in real-world scenarios.
What certificate will I get after completing this course?
Upon completing this course, you will receive a ProjectPro certification. This certificate validates your MLOps skills and demonstrates your ability to solve real-world business challenges through project-based assessments.
Is the MLOps course entirely online?
Yes, the MLOps course is 100% online. You can complete all the modules and projects remotely without needing in-person attendance. The online format allows you to learn at your own pace and on your own schedule.
Will I have access to course materials after completing the MLOps course?
Yes, once you complete the MLOps course, you will have ongoing access to course materials and resources. This allows you to revisit the content, review concepts, and stay updated with any new information or resources that may be added in the future.
How long does the MLOps course take to complete?
The duration of the MLOps course varies depending on your learning pace and schedule. On average, the course can be completed in 6 to 12 weeks. The time required will also depend on how much time you dedicate each week to studying and working on projects.
Will I have access to course materials after completing this ProjectPro course on Data Science?
Yes, after completing the ProjectPro Data Science course, you will continue to have access to course materials, projects, and resources. This ensures you can revisit the content anytime for review, practice, or applying the knowledge to real-world problems.
Learn how to build an ETL pipeline in Python using Spotify API, store it in BigQuery, and generate analytics-ready CSVs with full orchestration using Airflow.
As organizations increasingly rely on machine learning systems, the demand for Machine Learning Operations (MLOps) expertise is rising. The global MLOps market is expected to reach approximately USD 6.71 billion by 2027, growing at a remarkable CAGR of 44.6% from 2020 to 2027. With a significant rise in MLOps job openings, professionals skilled in MLOps practices are in high demand. Adding MLOps to your skill set enhances your career prospects and positions you for competitive salaries, with average earnings of approximately USD 14,500 and the potential for even higher rewards with experience. Thus, adding MLOps to your skill set can be highly beneficial. But why should you consider to master MLOps through a course with ProjectPro? Here are some compelling reasons:
Time-Saving
Online courses allow you to learn at your own pace and schedule, reducing the time spent commuting and allowing for more efficient use of your time. With the MLOps market growing so rapidly, getting up to speed quickly is crucial.
Expertise Involvement
Our courses are designed and taught by industry experts, ensuring you gain practical insights and best practices from seasoned MLOps professionals, software engineers, data engineering experts, and data scientists. This is critical as companies are increasingly prioritizing candidates with hands-on MLOps experience.
Comprehensive Learning
Online MLOps training with ProjectPro offers a structured curriculum that covers all essential aspects of MLOps, from basic concepts to advanced techniques, ensuring a thorough understanding of the subject. Given the projected increase in companies implementing MLOps practices by 2025 to be close to 50%, this comprehensive learning approach is the need of the hour.
Global Access
With online MLOps courses, you can access quality education from anywhere worldwide, breaking geographical barriers and opening up global learning and networking opportunities.
MLOps Skills Acquired from this Online MLOps Course
Mastering Machine Learning Operations (MLOps) requires a blend of diverse skills that bridge the gap between data science and IT operations. To excel in this field, one must develop proficiency in several key areas:
A strong command of programming languages like Python and R is essential for building and managing machine learning models.
Understanding machine learning fundamentals, including algorithms, model training, validation, and deployment processes, forms the backbone of MLOps expertise.
Proficiency in data engineering skills such as data preprocessing, ETL (Extract, Transform, Load) pipelines, and database management ensures smooth data flow and accessibility.
Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud enables scalable and efficient deployment of ML models.
Knowledge of DevOps concepts such as CI/CD pipelines, containerization tools like Docker, and orchestration platforms like Kubernetes is crucial for automating and streamlining operations.
Skills in setting up monitoring systems and analyzing logs help in maintaining model performance and reliability.
Utilizing version control tools like Git for tracking changes in code and models ensures reproducibility and collaboration.
Developing these skills not only enhances one's ability to implement robust MLOps solutions but also positions professionals to tackle complex challenges in deploying and maintaining machine learning systems effectively.
What will you Learn from this MLOps Course?
Our MLOps course modules are designed to provide a thorough understanding of machine learning operations, from foundational concepts to advanced techniques. Each course offers a detailed syllabus that covers key areas essential for mastering MLOps.
The curriculum is structured to guide you through every stage of the MLOps lifecycle, including building and deploying ML models, managing them in production environments, and scaling operations effectively. Focusing on practical skills and real-world machine learning applications, our MLOps courses ensure you gain the expertise needed for successful MLOps practice and to excel in the field. Explore our courses to find the course that best fits your MLOps journey, learning needs, and career goals.
MLOps Full Course Syllabus
The ProjectPro MLOps Full Course is designed to provide a comprehensive understanding of machine learning operations from scratch. This course covers all essential topics, helping you build a solid foundation in ML and MLOps. You'll learn about the basics of machine learning, including supervised, unsupervised, and reinforcement learning. The course then delves into data preprocessing techniques, feature engineering, and experiment tracking at a scale.
Key MLOps Concepts Covered
Basics of Machine Learning (Module 1)
Fundamental concepts of machine learning, including supervised, unsupervised, and reinforcement learning.
Building Machine Learning Models (Module 2)
Techniques for constructing robust ML models, focusing on model selection, training, and evaluation.
Machine Learning Model Deployment Strategies (Module 3)
Strategies for deploying ML models in various environments, ensuring they function efficiently in production.
Monitoring Machine Learning Models in Production (Module 4)
Techniques for monitoring model performance, detecting issues, and ensuring model reliability over time.
Scaling and Automation (Module 5)
Advanced methods for scaling ML operations and automating workflows to handle large datasets and complex models.
Each MLOps course module is developed to provide detailed insights and hands-on experience with relevant MLOps tools and techniques, ensuring you're well-prepared for real-world scenarios.
Become an MLOps Expert with ProjectPro’s Project-Based MLOps Crash Course
ProjectPro's MLOps Crash Course is tailored for those looking to grasp the fundamentals of MLOps quickly and prepare for job interviews. It focuses on the most challenging and important topics from each module, providing a swift yet thorough revision.
Core MLOps Concepts Covered
Quick overview of machine learning basics (Module 1)
Explore supervised, unsupervised, and reinforcement learning with projects such as building a similar images finder and regression models.
Essential model deployment techniques (Module 3)
Gain hands-on experience with model deployment strategies, containerization using Docker, and CI/CD pipelines through projects on deploying Mask R-CNN and ARIMA models.
Key aspects of maintaining and monitoring models (Module 4)
Learn about model monitoring techniques, handling data drift, and using tools like Airflow and Docker for end-to-end ML model monitoring.
These course modules are perfect for those needing a rapid yet comprehensive review of crucial MLOps basics and concepts. However, completing all modules is recommended for full proficiency and certification.
Simple MLOps Course Modules for Beginners
The MLOps Course Modules for Beginners are designed to introduce newcomers such as computer science graduate students, data analysis professionals, software engineering students, etc., to the world of machine learning and MLOps. It provides a basic understanding of the machine learning lifecycle leading to a solid starting point for further learning.
Key MLOps Concepts Covered
Introduction to Machine Learning (Module 1)
Understand basic concepts of machine learning, including supervised, unsupervised, and reinforcement learning.
Building First ML Model (Module 2)
Learn data quality assessment, feature engineering, and experiment tracking with projects focused on constructing an end-to-end ML pipeline.
Machine Learning Model Deployment Strategies (Module 3)
Explore deployment preparation, runtime environments, and containerization with practical projects on model deployment.
This beginner-friendly course is ideal for those new to the field, providing a strong foundation to build upon. But please note that for full mastery and certification, completing all the modules is necessary.
Advanced MLOps Training Course Modules
The Advanced MLOps Training Course is intended for professionals (data engineers/computer science experts/software developers/data science professionals) looking to deepen their knowledge and skills in MLOps. It focuses on advanced techniques for maintaining ML models in production, scaling, and automating ML workflows.
Advanced MLOps Concepts Covered
Maintaining ML Models in Production (Module 4)
Learn about model monitoring techniques and retraining strategies to address data drift and ensure consistent performance. Understand the various MLOps maturity levels and how to progress through them effectively.
Scaling and Automation (Module 5)
Master strategies for scaling machine learning workflows and automating ML pipelines. You'll work with powerful orchestration tools like Apache Airflow and Prefect to automate and streamline your ML operations, ensuring efficiency and reliability at scale.
This course equips you with the advanced technical skills to handle complex MLOps challenges and implement efficient, scalable, and robust ML solutions. As stated before, to achieve the ProjectPro certification, you must complete all the modules.
ProjectPro’s MLOps Certification Course - Path To Industry Expertise
The MLOps Certification Course at ProjectPro is designed to simulate real work experience through project-based learning. The projects you complete with us are as valuable as real-world experience, giving you the opportunity to solve practical business challenges and showcase your skills in job interviews or with your internal teams.
Here’s how the process works:
We’ll provide a structured learning path tailored to your chosen domain. This path will guide you through learning and applying critical concepts over 6-12 weeks, depending on your schedule.
Once you’ve completed the learning path, you’ll be assigned a comprehensive project to test your skills. This project will require you to apply everything you’ve learned, solving a business use case from start to finish.
After you submit your project, our experts will assess it and offer feedback for any necessary modifications. Once your project meets our standards, you’ll receive a certification that validates your MLOps expertise.
This MLOps certification process is centered around project-based assessments, ensuring that you develop the practical MLops skills required for successful MLOps implementation. Each module in our courses is integral to your preparation, covering everything from machine learning basics to advanced techniques in model deployment, monitoring, and scaling.
Specialized MLOps Courses
Our specialized MLOps course modules cover the MLOps tools and services provided by leading cloud platforms, ensuring you gain expertise in the platform of your choice. These courses detail the tools necessary for effective MLOps data pipelines and comprehensively demonstrate how our modules cover them.
AWS MLOps Course Modules
Learn about AWS services such as SageMaker, CodePipeline, and CloudWatch and how they integrate into the MLOps lifecycle. The modules cover practical examples of using these tools for model training, deployment, monitoring, and scaling.
Explore Azure Machine Learning, DevOps, and Monitor, and understand their role in MLOps. These modules provide a deep plunge into the pool of Azure services for building, deploying, and maintaining ML models.
Master Google Cloud Platform (GCP) services include AI Platform, Kubeflow, and Stackdriver. These modules will teach you to leverage these tools for efficient MLOps practices, from model development to deployment and monitoring on Google Cloud.
Each specialized course includes practical MLOps projects and hands-on modules that provide real-world experience and help you build a robust portfolio of MLOps skills.
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