MLOps with Azure
Master the art of deploying machine learning models with our expertly designed course. Gain unparalleled insights into Azure Machine Learning operations under the guidance of industry leaders. This comprehensive program equips you with essential skills in continuous integration/continuous deployment pipelines tailored specifically for Azure environments. Enroll now to transform your capabilities in machine learning operations.
- Available in:
- Malaysia

Corporate Pricing
Pax:
Training Provider Pricing
Pax:
Features
Classification
Focus Area Course
- Addresses skill gaps across industries
- Emphasizes emerging technologies and practices
- Enhances workforce capabilities
- Verified by industry experts
- Broadly applicable across sectors
Subsidies

What you'll learn
- Identify key challenges in machine learning deployment patterns.
- Gain proficiency in AI platform pipelines and their ecosystems.
- Create and manage CI/CD pipelines within Azure environments.
- Understand the complete machine learning lifecycle and architecture.
- Deploy high-performance machine learning models effectively.
- Implement MLOps principles using Azure Machine Learning tools.
- Develop skills in data definition, baseline establishment, and label consistency.
Why should you attend?
This course provides a comprehensive exploration of the machine learning lifecycle, architecture, and roles, offering insights into the responsibilities involved in developing effective machine learning solutions. Participants will delve into the fundamentals of machine learning, addressing key challenges and deployment patterns while gaining expertise in pipeline monitoring to ensure robust model performance. The curriculum further explores AI platform pipelines, guiding learners on when to use them and understanding their ecosystem. A significant focus is placed on data definition and establishing baselines, covering major types of data, small data considerations, and ensuring label consistency for accurate model training. Participants will engage in hands-on training to build models, with modules dedicated to project deployment and error analysis. The course emphasizes prioritizing tasks and managing skewed datasets effectively. Performance auditing and data-centric AI development are also covered, along with techniques for data augmentation. Incorporating MLOps principles, the program outlines standard practices and implementation strategies that highlight the benefits of MLOps. Learners will gain practical experience with Kubeflow pipelines, exploring system concepts and creating custom components. The course culminates with an in-depth look at Azure Machine Learning, focusing on Azure DevOps integration and ML connections. Participants will learn to manage CI/CD MLOps pipelines within Azure, mastering continuous integration scripts and deployment processes. Finally, learners will explore advanced topics such as neural architecture search and high-performance modeling for deploying machine learning models effectively.
Course Syllabus
Day 1 - ML Fundamentals and Training
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 1
Day 2 - MLOps and Pipeline Implementation
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 2
Day 3 - Azure ML Production Deployment
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 3
Ratings and Reviews
Instructor
Tarun Sukhani is a distinguished professional trainer and consultant with nearly 30 years of experience in the IT and business sectors, having worked internationally across AMER, APAC, and EMEA. His expertise spans a wide array of domains such as Agile methodologies (Scrum, SAFe, Kanban), enterprise architecture frameworks like TOGAF and COBIT, IT service management standards including ITIL and ISO27001, as well as cybersecurity certifications like CISO and CISSP. Tarun's proficiency extends to project management frameworks such as PRINCE2 and PMP, along with cutting-edge technologies in Big Data analytics using Hadoop and Spark, data science with Python or R, and data visualization tools like Tableau. Tarun has held numerous senior development and executive roles including CIO/CTO positions where he managed large-scale IT operations for multinational corporations such as Dell, AMD, and Experian. His leadership skills have been instrumental in enhancing business operations across various functions including HR, Finance, Operations, Sales, Risk Management, Engineering/Manufacturing, and Accounting. He has also contributed significantly to regional conglomerates like Indra in the Asia Pacific region. A passionate educator at heart, Tarun has facilitated training workshops throughout Asia Pacific countries such as Malaysia, Indonesia, Philippines, Thailand, and Singapore. His training sessions cover a broad spectrum of topics from project management to strategic leadership and soft skills development. Additionally, he specializes in advanced technical subjects like software architecture design patterns for reactive microservices architectures on cloud platforms. Tarun's academic credentials are equally impressive; he graduated summa cum laude with an MSc in Information Systems and an MBA in Finance and Operations Management from Loyola University Chicago. He holds multiple Bachelor's degrees in Biology, Math & Computer Science alongside Business Administration. Further enriching his knowledge base are certifications as an Agile/Scrum trainer; Java/.NET programmer; Machine Learning specialist; InfoSec expert; Business Intelligence professional; complemented by advanced studies in AI & Blockchain from prestigious institutions like MIT & Stanford. His client portfolio includes renowned organizations such as Western Digital/Sandisk for machine learning product management projects; Singtel & CIMB for agile product development initiatives; Tenaga Nasional & JPJ for agile project management engagements among others. Tarun's dynamic approach combined with his deep-rooted passion for developing people makes him a sought-after speaker at international conferences where he shares insights on digital transformation strategies.
Instructor
Mohammad Mehdi Lotfinejad is an accomplished Chief Data Officer with a profound expertise in data science and engineering, amassing over ten years of experience in developing data processing pipelines for enterprise insights. He is a proven leader with exceptional communication, presentation, and leadership skills, certified as an HRDF trainer with more than 15 years of experience as a computer science instructor both in academia and as a professional data science/engineering trainer in the industry. His academic credentials include a PhD in Computer Science from Universiti Malaya, Malaysia, and he holds certifications from Harvard Business School in Business Analytics. Mohammad specializes in cutting-edge technologies such as Apache Spark, MySQL, PostgreSQL, MongoDB, Snowflake, Redshift, Apache Airflow, API and Microservices, and Amazon Web Services. Currently serving as the Chief Data and Knowledge Officer at Magna.ai since February 2024, Mohammad leads the development of graph databases and data warehouses to support AI-driven law case analysis services. He architects robust API and microservice solutions to enhance system interoperability and scalability while ensuring data security and compliance with legal standards. Prior to this role, he has been contributing his expertise as a Senior Data Engineer at AXIATA Digital Advertising (ADA) since March 2020. Here, he collaborates on designing automated data pipelines using AWS RedShift and Snowflake for storing telco data and implements BI dashboards leveraging Google BigQuery. From June 2018 to February 2020, Mohammad was the Lead Senior Data Scientist Professional Trainer at The Center of Applied Data Science in Kuala Lumpur. He led teams of data scientists and engineers to design professional training programs for prominent clients like CIMB, PETRONAS, SHELL, and TNB. His earlier roles include leading big data engineering teams at RAHA in Iran where he developed large-scale analytics pipelines using Hadoop Ecosystem tools like Hive and Spark. In academia, Mohammad served as a faculty member at Payame Noor University from September 2014 to June 2018 where he supervised graduate research projects and contributed significantly to curriculum development. His tenure also includes leadership positions at Islamic Azad University where he managed departments to achieve high academic standards. With technical proficiencies spanning RDBMS like MySQL and PostgreSQL to programming languages such as Python and C++, Mohammad is adept at web design using HTML/CSS/Bootstrap alongside project management skills including Scrum Master certification. His published works include books on Object-Oriented Programming and Project Management Fundamentals along with numerous journal articles on topics ranging from solar radiation prediction models to machine learning algorithms for intrusion detection systems.
Minimum Qualification
Target Audience
Methodologies
FAQs
- Public pricing: applies for individuals signing up from different companies.
- Corporate pricing: applies if a company wants to have an intake for its employees only.
- Training provider pricing: applies only for other training providers looking to hire our trainers and use our content. Our content has a licensing fee.
Why should you attend?
This course provides a comprehensive exploration of the machine learning lifecycle, architecture, and roles, offering insights into the responsibilities involved in developing effective machine learning solutions. Participants will delve into the fundamentals of machine learning, addressing key challenges and deployment patterns while gaining expertise in pipeline monitoring to ensure robust model performance. The curriculum further explores AI platform pipelines, guiding learners on when to use them and understanding their ecosystem. A significant focus is placed on data definition and establishing baselines, covering major types of data, small data considerations, and ensuring label consistency for accurate model training. Participants will engage in hands-on training to build models, with modules dedicated to project deployment and error analysis. The course emphasizes prioritizing tasks and managing skewed datasets effectively. Performance auditing and data-centric AI development are also covered, along with techniques for data augmentation. Incorporating MLOps principles, the program outlines standard practices and implementation strategies that highlight the benefits of MLOps. Learners will gain practical experience with Kubeflow pipelines, exploring system concepts and creating custom components. The course culminates with an in-depth look at Azure Machine Learning, focusing on Azure DevOps integration and ML connections. Participants will learn to manage CI/CD MLOps pipelines within Azure, mastering continuous integration scripts and deployment processes. Finally, learners will explore advanced topics such as neural architecture search and high-performance modeling for deploying machine learning models effectively.
What you'll learn
- Identify key challenges in machine learning deployment patterns.
- Gain proficiency in AI platform pipelines and their ecosystems.
- Create and manage CI/CD pipelines within Azure environments.
- Understand the complete machine learning lifecycle and architecture.
- Deploy high-performance machine learning models effectively.
- Implement MLOps principles using Azure Machine Learning tools.
- Develop skills in data definition, baseline establishment, and label consistency.
Course Syllabus
Day 1 - ML Fundamentals and Training
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 1
Day 2 - MLOps and Pipeline Implementation
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 2
Day 3 - Azure ML Production Deployment
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 3
Corporate Pricing
Pax:
Training Provider Pricing
Pax:
Features
Classification
Focus Area Course
- Addresses skill gaps across industries
- Emphasizes emerging technologies and practices
- Enhances workforce capabilities
- Verified by industry experts
- Broadly applicable across sectors
Subsidies

Ratings and Reviews
Instructors
Tarun Sukhani is a distinguished professional trainer and consultant with nearly 30 years of experience in the IT and business sectors, having worked internationally across AMER, APAC, and EMEA. His expertise spans a wide array of domains such as Agile methodologies (Scrum, SAFe, Kanban), enterprise architecture frameworks like TOGAF and COBIT, IT service management standards including ITIL and ISO27001, as well as cybersecurity certifications like CISO and CISSP. Tarun's proficiency extends to project management frameworks such as PRINCE2 and PMP, along with cutting-edge technologies in Big Data analytics using Hadoop and Spark, data science with Python or R, and data visualization tools like Tableau. Tarun has held numerous senior development and executive roles including CIO/CTO positions where he managed large-scale IT operations for multinational corporations such as Dell, AMD, and Experian. His leadership skills have been instrumental in enhancing business operations across various functions including HR, Finance, Operations, Sales, Risk Management, Engineering/Manufacturing, and Accounting. He has also contributed significantly to regional conglomerates like Indra in the Asia Pacific region. A passionate educator at heart, Tarun has facilitated training workshops throughout Asia Pacific countries such as Malaysia, Indonesia, Philippines, Thailand, and Singapore. His training sessions cover a broad spectrum of topics from project management to strategic leadership and soft skills development. Additionally, he specializes in advanced technical subjects like software architecture design patterns for reactive microservices architectures on cloud platforms. Tarun's academic credentials are equally impressive; he graduated summa cum laude with an MSc in Information Systems and an MBA in Finance and Operations Management from Loyola University Chicago. He holds multiple Bachelor's degrees in Biology, Math & Computer Science alongside Business Administration. Further enriching his knowledge base are certifications as an Agile/Scrum trainer; Java/.NET programmer; Machine Learning specialist; InfoSec expert; Business Intelligence professional; complemented by advanced studies in AI & Blockchain from prestigious institutions like MIT & Stanford. His client portfolio includes renowned organizations such as Western Digital/Sandisk for machine learning product management projects; Singtel & CIMB for agile product development initiatives; Tenaga Nasional & JPJ for agile project management engagements among others. Tarun's dynamic approach combined with his deep-rooted passion for developing people makes him a sought-after speaker at international conferences where he shares insights on digital transformation strategies.
Mohammad Mehdi Lotfinejad is an accomplished Chief Data Officer with a profound expertise in data science and engineering, amassing over ten years of experience in developing data processing pipelines for enterprise insights. He is a proven leader with exceptional communication, presentation, and leadership skills, certified as an HRDF trainer with more than 15 years of experience as a computer science instructor both in academia and as a professional data science/engineering trainer in the industry. His academic credentials include a PhD in Computer Science from Universiti Malaya, Malaysia, and he holds certifications from Harvard Business School in Business Analytics. Mohammad specializes in cutting-edge technologies such as Apache Spark, MySQL, PostgreSQL, MongoDB, Snowflake, Redshift, Apache Airflow, API and Microservices, and Amazon Web Services. Currently serving as the Chief Data and Knowledge Officer at Magna.ai since February 2024, Mohammad leads the development of graph databases and data warehouses to support AI-driven law case analysis services. He architects robust API and microservice solutions to enhance system interoperability and scalability while ensuring data security and compliance with legal standards. Prior to this role, he has been contributing his expertise as a Senior Data Engineer at AXIATA Digital Advertising (ADA) since March 2020. Here, he collaborates on designing automated data pipelines using AWS RedShift and Snowflake for storing telco data and implements BI dashboards leveraging Google BigQuery. From June 2018 to February 2020, Mohammad was the Lead Senior Data Scientist Professional Trainer at The Center of Applied Data Science in Kuala Lumpur. He led teams of data scientists and engineers to design professional training programs for prominent clients like CIMB, PETRONAS, SHELL, and TNB. His earlier roles include leading big data engineering teams at RAHA in Iran where he developed large-scale analytics pipelines using Hadoop Ecosystem tools like Hive and Spark. In academia, Mohammad served as a faculty member at Payame Noor University from September 2014 to June 2018 where he supervised graduate research projects and contributed significantly to curriculum development. His tenure also includes leadership positions at Islamic Azad University where he managed departments to achieve high academic standards. With technical proficiencies spanning RDBMS like MySQL and PostgreSQL to programming languages such as Python and C++, Mohammad is adept at web design using HTML/CSS/Bootstrap alongside project management skills including Scrum Master certification. His published works include books on Object-Oriented Programming and Project Management Fundamentals along with numerous journal articles on topics ranging from solar radiation prediction models to machine learning algorithms for intrusion detection systems.
Minimum Qualification
Target Audience
Methodologies
FAQs
- Public pricing: applies for individuals signing up from different companies.
- Corporate pricing: applies if a company wants to have an intake for its employees only.
- Training provider pricing: applies only for other training providers looking to hire our trainers and use our content. Our content has a licensing fee.
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