According to deeplearning.ai, only 22% of companies using machine learning have successfully deployed a model. The needs for ML Engineers are growing exponentially as the industry moves towards Data-centric AI. ML Engineering (MLOps) is at the intersection of Machine Learning, DevOps, and Data Engineering. It is a critical role that makes sure the AI products get deployed in production in a scalable and reliable way.
If you’re want to take your ML skills to the next level, this ML Engineer Bootcamp was created for professionals like you who want to sharpen your skills in deep learning, computer vision, NLP, big data, and MLOps.
Interested? Inquire about the curriculum or talk to our program advisor.
We understand that there are theoretical underpinnings to cover. Most importantly, we know that we need to head beyond the classroom to truly work in this field. For example, by rolling up our sleeves and finding a way to package our work, tuning and molding a model to different setups, whether they be predictions with a CPU, an industrial-grade embedded system, or a beefy datacenter GPU like the A100.
In this advanced program, you learn deep learning techniques, use cases in computer vision and NLP, and the engineering and operations side that allows you to appreciate the entire lifecycle of ML projects from data preparation to model deployment and monitoring.
Whether you want to engage in a custom capstone project or engage with scenarios that mirror our work in consultancy we have you covered. In this 6-month part-time bootcamp, you will get fully immersed in learning the cutting-edge machine learning and deep learning techniques as well as end-to-end machine learning operations. The program has two semesters:
Semester 1: Deep Learning (theory, frameworks, computer vision, NLP)
Semester 2: Use Cases (Recommender systems, Time series), MLOps (model packaging, deployment, CI/CD, monitoring, GPU tuning, edge deployment)
You will be working with our expert instructors on several capstone projects including DeepRacer, Lane Detection, Background Removal, etc. Students in the full-time delivery option will also work with our AI project managers on real client projects.
WeCloudData partners with PayBright to offer our students different payment plans
With Ontario Second Career grant you may be eligible for up to $28,000 for costs including:
tuition, books, manuals, transportation, basic living allowance, child care.
Students in Ontario, Canada can apply for student line of credit from Bank of Montreal (BMO) with low interest rate.
Thank you for interested in our courses. You can now download the Course Package.