Intro to Machine Learning in AWS for Beginners - New 2022!
- Basic knowledge in AWS
- Basic knowledge in machine learning
Machine Learning is the future one of the top tech fields to be in right now!
ML and AI will change our lives in the same way electricity did 100 years ago. ML is widely adopted in Finance, banking, healthcare, transportation, and technology.
The field is exploding with opportunities and career prospects.
This introductory course is for absolute beginners, students will learn:
Key AWS services such as Simple Storage Service (S3), Elastic Compute Cloud (EC2), Identity and Access Management (IAM) and CloudWatch,
The benefits of cloud computing and what’s included in the AWS Free Tier Package
How to setup a brand-new account in AWS and navigate through the AWS Management Console
The fundamentals of Machine Learning and understand the difference between Artificial Intelligence (AI), Machine Learning (ML), Data Science (DS) and Deep Learning (DL)
List the key components to build any machine learning models including data, model, and compute
Learn the fundamentals of Amazon SageMaker, SageMaker Components, training options offered by SageMaker including built-in algorithms, AWS Marketplace, and customized ML algorithms
Cover AWS SageMaker Studio and learn the difference between AWS SageMaker JumpStart, SageMaker Autopilot and SageMaker Data Wrangler
Learn how to write our first code in the cloud using Jupyter Notebooks.
We will then have a tutorial covering AWS Marketplace object detection algorithms such as Yolo V3
Learn how to train our first machine learning model using the brand-new AWS SageMaker Canvas without writing any code!
Who this course is for:
- Absolute Beginners who want to break into machine learning in AWS
- Beginners Data Scientists wanting to advance their careers by Learning AWS and Machine Learning
- Tech enthusiasts who are passionate and new to Machine Learning and want to gain basic knowledge in AWS & Machine Learning
Ryan Ahmed is a best-selling Udemy instructor who is passionate about education and technology. Ryan's mission is to make quality education accessible and affordable to everyone. Ryan holds a Ph.D. degree in Mechanical Engineering from McMaster* University, with focus on Mechatronics and Electric Vehicle (EV) control. He also received a Master’s of Applied Science degree from McMaster, with focus on Artificial Intelligence (AI) and fault detection and an MBA in Finance from the DeGroote School of Business.
Ryan held several engineering positions at Fortune 500 companies globally such as Samsung America and Fiat-Chrysler Automobiles (FCA) Canada. Ryan has taught several courses on Science, Technology, Engineering and Mathematics to over 300,000+ students globally. He has over 25 published journal and conference research papers on state estimation, AI, Machine learning, battery modeling and EV controls. He is the co-recipient of the best paper award at the IEEE Transportation Electrification Conference and Expo (iTEC 2012) in Detroit, MI, USA.
Ryan is a Stanford Certified Project Manager (SCPM), certified Professional Engineer (P.Eng.) in Ontario, a member of the Society of Automotive Engineers (SAE), and a member of the Institute of Electrical and Electronics Engineers (IEEE). He is also the program Co-Chair at the 2017 IEEE Transportation and Electrification Conference (iTEC’17) in Chicago, IL, USA.
* McMaster University is one of only four Canadian universities consistently ranked in the top 100 in the world.