Cloud AI & MLOps Specialization
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Course
Cloud AI & MLOps Specialization
Master Cloud AI and MLOps with real-world projects! Deploy, scale, and automate AI models on AWS and GCP to power cutting-edge applications.
Online Live Classes
Mentored
Intermediate
AI powers modern applications, and the demand for scalable, automated deployments has never been greater. This course equips you with the hands-on skills to deploy, scale, and automate machine learning models in the cloud using AWS and GCP.
In this course, you will explore AI model deployment, efficient ML workflow management, and MLOps best practices, including CI/CD pipelines, automated training, and real-world deployment strategies. You will also gain hands-on experience in containerization, orchestration, and continuous monitoring to ensure reliable AI performance in production environments.
By the end of the course, you will have a deep understanding of scalable, cloud-based AI solutions, preparing you for roles in AI engineering, data science, and DevOps. These skills will help you streamline AI operations and optimize models for automation, efficiency, and real-world impact.
This course comprises 2 purposely designed modules that take you on a carefully defined learning journey.
Our proven learning methodology blends the best that instructor-led training and self-paced learning have to offer. Leveraging the power of instructor feedback, mentor-supported hands-on practice, and additional home-based studying, you will build the deep technical and practical understanding todays employers are looking for.
Additionally, you will enjoy learning via an interactive online classroom environment where you will be able to participate and actively engage with your peers, instructors, and mentors. Plus, you will get the opportunity to earn recognized certifications which will help your resume and LinkedIn profile stand out.
The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include reading material, hands-on labs, and online exam questions.
As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues.
Once you have successfully completed the course, you will earn your Certificate of Completion.
By the end of this course, you will have:
- Deployed AI models on AWS, Azure, and Google Cloud.
- Automated AI pipelines using CI/CD best practices.
- Monitored AI models to track performance and detect drift.
- Machine learning engineers Deploying & scaling AI models in the cloud.
- Data scientists Automating ML workflows & optimizing model deployment.
- AI engineers Integrating MLOps best practices for production-ready AI.
- Cloud & DevOps engineers Expanding AI model deployment on AWS & GCP.
- Software engineers Building & managing scalable AI applications in the cloud.
- IT & system administrators Exploring cloud AI infrastructure & automation.
- AI product managers Understanding MLOps for AI model lifecycle management.
- Basic Python programming Familiarity with Python scripting and data handling.
- Fundamental machine learning knowledge Understanding of ML models, training, and evaluation.
- Basic cloud computing concepts Some experience with cloud platforms (AWS, GCP, or Azure) is helpful but not required.
- Familiarity with version control & CI/CD Exposure to Git and DevOps practices is beneficial.
Course Outline
Why Learn with SkillUp Online?
We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.
Reskilling into tech? We’ll support you.
Upskilling for promotion? We’ll help you.
Cross-skilling for your career? We’ll guide you.
Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
Designed by the industry for the industry so you can build job-ready skills.
Job-Ready Skills Focus
Competency building and global certifications employers are actively looking for.
FAQs
This course is ideal for machine learning engineers, data scientists, AI engineers, cloud and DevOps engineers, software engineers, IT administrators, and AI product managers looking to master cloud AI deployment and MLOps best practices.
Bootcamps focus on broad AI topics, whereas this specialization dives deep into cloud-based AI deployment, MLOps, and automation, making it ideal for professionals looking to streamline AI workflows at scale.
After completing this course, you can pursue roles such as:
- MLOps engineer: Automating ML workflows and CI/CD pipelines.
- AI cloud engineer: Deploying scalable AI models on AWS/GCP.
- Machine learning engineer: Managing cloud-based ML solutions.
- DevOps engineer (AI focus): Ensuring AI model reliability and scalability.
The curriculum covers cloud AI automation, MLOps best practices, CI/CD for ML, and real-world AI deploymentensuring learners gain industry-relevant skills.
Yes, you will earn an industry-recognized Certificate of Completion, validating your newly learned skills.
Course Offering
Type of certificate
Certificate of completion
About this course
02 Modules
12 Skills
Includes
Live Instructor-Led Sessions
Hands-On Projects
Quizzes & Labs
Community & Peer Support
Create
Deploy a Scalable AI Model on Kubernetes
Exercises to explore
Deploying an AI Model on AWS SageMaker
Implementing CI/CD for AI Pipelines
AI Model Monitoring with Mlflow
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