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Home / Data Engineering & Cloud Technologies / MLOps on Azure
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The past decade has seen an explosion in the world of data science and machine learning with a lot of companies investing in these fields. However, companies and data scientists quickly realized that while building a model is simple, deploying them at scale is the real challenge. Organizations today are trying to incorporate ML and AI in their applications by adopting MLOps to gain agility and serve the real-world online application. MLOps (Machine Learning Operations) facilitates the management of ML Lifecycle by integrating Data Science and Operations. It also helps in building, training, and deploying machine learning models and workflows to get to production faster. To gain in-depth insights on the fundamentals of MLOps, join the MLOps on Azure course from 360DigTMG.
INR 101,500 71,500
This course gives you insights into the architecture of MLOps in the Azure Machine Learning environment. It aims to impart knowledge on how to perform MLOps efficiently using Microsoft cloud-native tools such as Azure Machine Learning, Azure Machine Learning Studio, Databricks, MLflow, Kubeflow, Apache Airflow among others. Students will learn to build ML pipelines to design, deploy, and manage model workflows to drive efficiency and productivity with MLOps. Learn how monitoring and validation of machine learning models can speed up the pace of model development and deployment with MLOps. This course is designed for Data Scientist and Software Developers who wish to leverage Azure Machine Learning to facilitate MLOps practices. Join the ‘MLOps on Azure’ course with 360DigiTMG and learn to streamline and automate the machine learning life cycle by integrating DevOps processes. What is MLOps? Machine learning is quickly gaining a lot of traction and is becoming a technology that every company wants to implement but soon realize that creating and training an ML model is much easier than actually practically deploying that model. Machine Learning Operations (MLOps) is a discipline based on DevOps that accelerates the efficiency of workflows and enhances the quality of machine learning solutions.
MLOps facilitates the development, deployment, management, and governance of ML models in production environments. This course introduces students to MLOps tools and best practices for building reproducible workflows and machine learning models. This course aims to be a set of guiding principles for MLOps on Azure. Needless to say, it is the result of experts in the domain distilling their hard work and knowledge and putting together a comprehensive guide to enable ML practitioners and Data Scientists to deploy models with ease. The objective of this course is to introduce learners to the MLDC also known as the Machine Learning Development Cycle using open source frameworks like MLflow, Kubeflow, Apache Airflow, Azure Machine Learning, etc. Participants will also learn about containers like Docker and containerized platforms like Kubernetes. So, prepare yourself for more lucrative career options with Industry-relevant curriculums and hands-on Capstone Project in the MLOps on Azure course. The participants will also learn:
60 hours
Live Sessions
40 hours
Assignments
Live Projects
MLOps is a fast-growing subdomain of the larger AI/ML/DS domain. It is a portmanteau of the words Machine Learning (ML) and DevOps, signifying that this domain is essentially an intersection of these two different disciplines. While ML deals with the development of algorithms and models using statistical and machine learning techniques, DevOps is focused on deploying the (ML model or any other) software applications into production using the Continuous Delivery and Continuous Integration principles. There is a need for source control, reproducible ML pipelines, model versioning and storage, model packaging, validation, deployment, and monitoring. Besides, there is also a need for model retraining based on the results of the monitoring activities. Currently, MLOps is being thought of as a concept, not a product or a service although a lot of effort is being put into either productizing it or providing it as a service. This course aims to introduce everyone to MLOps done right using Azure with Azure Machine Learning, MLflow, Databricks, and Kubeflow.
Data Scientists and ML practitioners usually are good at building models and performing complex statistical analysis but may not be good at software engineering skills required to put them into production. Also, a simple DevOps approach is not sufficient to address an ML project. It needs to take into account models, data, experiments, runs and artifacts produced. By way of this module we explore how model deployment is being done now vs how could the ideal state be.
Azure Machine Learning (AML) which is a cloud service offering has built-in MLOps. It can easily take care of the different phases of the Machine Learning Development Cycle (MLDC) and also offers complete integration right out of the box with popular ML frameworks like Scikit-learn, Pytorch, Tensorflow and MXNet. This module will provide a deeper look into how AML provides support for all the different phases of the MLDC.
Using Azure Pipelines, ML Engineers can automatically build and test ML projects. It seamlessly integrates CI (Continuous Integration) and CD (Continuous Delivery) and ships the ML model and supporting code to a target of choice. Azure Pipelines also facilitates CT (Continuous Testing) by helping automate the build, test and deploy processes efficiently.
Docker is a containerization mechanism to package the code and the underlying runtime as a Docker image to enable modularity and portability. The aim is to remove the occurrences of ‘it worked on my laptop’ by containerizing all the required elements of the model. Kubernetes is a container orchestration platform which helps in scheduling and orchestrating all the workloads among the different containers.
Understand how Azure ML helps in deploying the ML models by 1. ensuring that the source code is controlled, 2. Creating reproducible training cycles 3. Data and Environment management 4. Creating and maintaining ML pipelines 5. Utilizing model registry to track models and experiments 6. Evaluate and Validate the model 7. Monitor and retrain it as needed
MLflow is an open-source platform which can run on Azure (or any other public cloud or on-prem infrastructure) which also helps in managing the ML lifecycle. Understand the 4 major components
Kubeflow is another open-source framework for MLOps which is gaining popularity very quickly. It is a framework which works on top of the Azure Kubernetes Service (AKS) and helps in orchestrating the different phases on MLDC without a lot of overhead of managing low level Kubernetes APIs. This module teaches how KFserving, Knative and other sub components of Kubeflow work on Azure to create another awesome MLOps framework.
The MLOps market is expected to grow to nearly US$4.1 billion by 2025. MLOps connects the development of the machine learning model and implements it in production. Linking these disparate areas of machine learning requires the right team, continuous integration, and deployment of data along with collaboration and communication between data scientists, developers and platform engineers.
AI and ML practices are soon becoming an intrinsic part of many modern-day business applications. But most organizations have not been successful in delivering AI-based applications and are only hamstrung with transforming data Science models into interactive applications capable of working with large data sets. To address this challenge a new practice called MLOps has emerged that integrates the AI/ML capabilities with DevOps practices. It aims to continuously develop and deliver data along with ML applications. So one of the trends we are going to see will be an increase in the demand for hybrid AI deployments and organizations will use accessible and production-ready data-science platforms.
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Earn a certificate and demonstrate your commitment to the profession. Use it to distinguish yourself in the job market, get recognised at the workplace and boost your confidence. The MLOps on Azure Course Certificate is your passport to an accelerated career path.
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"The training was organised properly, and our instructor was extremely conceptually sound. I enjoyed the interview preparation, and 360DigiTMG is to credit for my successful placement.”
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"Although data sciences is a complex field, the course made it seem quite straightforward to me. This course's readings and tests were fantastic. This teacher was really beneficial. This university offers a wealth of information."
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Data Scientist
"The course's material and infrastructure are reliable. The majority of the time, they keep an eye on us. They actually assisted me in getting a job. I appreciated their help with placement. Excellent institution.”
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Kadar Nagole
"Excellent team and a good atmosphere. They truly did lead the way for me right away. My mentors are wonderful. The training materials are top-notch.”
Gowtham R
Data Engineer
"The instructors improved the sessions' interactivity and communicated well. The course has been fantastic.”
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"The instructors went above and beyond to allay our fears. They assigned us an enormous amount of work, including one very difficult live project. great location for studying.”
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Basic Degree is required. Basic knowledge of Maths and Statistics is needed to learn the tools.
More than 20 assignments are provided for the students to make them proficient. A dedicated team of mentors will guide the students throughout their learning process.
MLOps is needed to enhance the machine learning-driven applications in business. This enables Data Scientists to concentrate on their work and empowers MLOps engineers to take responsibility and handle machine learning in production.
Machine Learning operations are considered to be the most valuable practices any company can have. It helps in improving quality and delivering better performance.
We provide a career coach to help you to build your portfolio and prepare you for facing interviews. Job placement Assistance.
Yes, you can attend a free demo class and can interact with the trainer to clarify your queries.
Yes, students will be given more than 3 real-time projects under the guidance of industry experts.
Students after completing the course will be prepared for interviews. Guidance will be given by conducting mock interviews and questionnaires. This session will help students to boost their confidence and improve their communication skills.
We provide online training with flexible timings along with online sessions.
You can clarify your doubts with trainers, and mentors are provided for the students to whom you can approach at any time.
You will be given LMS access, which helps you to revise the course and if you miss any class you can see the recorded version of the class. You can attend webinars for free that will be conducted on trending topics for a lifetime and many more.
The various job profiles include Machine Learning Engineer, Machine Learning Analyst, NLP Data Scientist, Data Scientist, Data Mining Specialists, Cloud Architects, and Machine Learning Scientist, etc.
Tech-roles, particularly in the field of Data Science, ML and AL are gaining importance. A fresher in this field can fetch anything between ? 599,807- 791,326 and an experienced ML professional can get 13 to 22 lakhs per annum.
Practical insight into any technology is only possible through projects that help you master the technology. Some of the projects that one can undertake to gain practical experience include ‘Performing Data Visualization on Uber Data’ or ‘Game Prediction Project’ that involves predicting the interest of the users.
The various open-source MLOps tools give users and organizations a platform to collaborate. Some open-source tools include MetaFlow, MLRun, ML flow, MLReef, Seldon, etc.
The course is designed to suit the needs of students as well as working professionals. We at 360DigiTMG give our students the option of interactive live online learning. We also support e-learning as part of our curriculum.
Machine Learning and AI are increasingly becoming key agents that are transforming the performance of businesses today who are leveraging the capabilities of MLOps for quicker deployment of ML models.
360DigiTMG offers customised corporate training programmes that suit the industry-specific needs of each company. Engage with us to design continuous learning programmes and skill development roadmaps for your employees. Together, let’s create a future-ready workforce that will enhance the competitiveness of your business.
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4.8
I've reached a major milestone in my Data Analytics internship with 360DigiTMG. With guidance from experienced mentors, they’ve really helped me get closer to reaching my goals. Embrace the valuable knowledge and skills gained and continue leveraging this opportunity to excel in the dynamic field of data analytics.
I'm Sai Manikanta, delighted to share my internship journey at 360DigiTMG. This internship has been a great opportunity for me to expand my limits and gain new skills. Diverse activities provided profound insights, shaping a promising future. Grateful for this opportunity, I eagerly anticipate forthcoming outcomes.
The data analytics program was truly outstanding! The meticulously structured classes and enthusiastic instructors made learning both enjoyable and engaging. With this extensive knowledge at my disposal, I am not only confident but also eager to make significant strides in the field of data analytics.
One of the best institutes for training in Hyderabad. I am done with the Data science and Machine Learning course here. Trainers are highly educational and instructive. Invaluable experience gained through live projects, enhancing technical familiarity. Additional value provided through helpful working sessions further enriches the learning journey.
The teacher and staff are highly skilled at their jobs. They teach in a way that's easy to understand and interesting. They know a lot about the subject, so learning from them is great. The teacher plans everything well and explains hard stuff with lots of examples using Excel.
It was a wonderful experience for me as an intern to work in 360digitmg. This internship had made me become an expert in the field of data analytics which had greatly motivated me and Working with real-time datasets provided invaluable experience, enhancing my skills significantly.
It was an awesome experience at 360Digitmg, offering the best resources and fostering excellent interaction. Working on real-life projects under expert supervision provided invaluable learning opportunities. Overall, it was a highly rewarding learning experience that contributed significantly to my growth and career advancement.
I found a great coaching institute in Chennai for data-related courses. I completed a successful data analytics program there. The trainers were skilled and supportive, especially Vijay, who made learning Python easy. Thanks to him and 360DigiTMG. I also learned Data Analytics with SQL, Tableau, and Excel.
360DigiTMG institute offers an exceptional learning experience, excelling in data science and machine learning. Despite lacking coding background, tutors ensured effective learning, making concepts easily understandable. Tutorial sessions covered job interview prep and case studies, with Mind maps boosting confidence. Highly recommend this Bangalore institute for data-related courses.
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360DigiTMG institute offers one place where the course curriculum is so good and teacher training, equipping students with skills for their dream job. Grateful for the internship experience, including live projects, resume building, presentation practice, and interview preparation sessions. Enhanced confidence for future interviews. Thank you, 360DigiTMG, for the invaluable learning journey.
The data analytics with python course in the best coaching centre in Chennai. Finished the course well and worked on practical tasks. This helped me build my professional experience. By participating in interview preparation and project presentation sessions, I realized that I could present myself confidently to an interview.
During my internship at 360DigiTMG, I gained invaluable experience, expanding my knowledge significantly. The opportunity provided a rich learning environment, fostering personal and professional growth. Grateful for the wonderful experience and the skills acquired, which will undoubtedly shape my future endeavours.
Great institute! Exceptional learning experience, especially in data science and machine learning. Tutors adeptly simplified complex concepts despite my coding limitations. Varied tutorial sessions prepared us for job interviews with insightful case studies. Mind maps boosted confidence. Highly recommend this Bangalore-based institute for data-related courses.
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