Udemy AWS Certified Machine Learning Specialty (MLS-C01)

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What you'll learn:

• You will gain first-hand experience on how to train, optimize, deploy, and integrate ML in AWS cloud
• AWS Built-in algorithms, Bring Your Own, Ready-to-use AI capabilities
• Complete Guide to AWS Certified Machine Learning – Specialty (MLS-C01)
• Includes a high-quality Timed practice test (a lot of courses charge a separate fee for practice test)
• Zero Downtime Model Deployment
• How to Integrate and Invoke ML from your Application
• Automated Hyperparameter Tuning

Requirements:

• Familiarity with Python
• AWS Account - I will walk through steps to setup one
• Basic knowledge of Pandas, Numpy, Matplotlib
• Be an active learner and use course discussion forum if you need help - Please don't put help needed items in course review

Description:



Learn about cloud based machine learning algorithms, how to integrate with your applications and Certification Prep*** NEW Labs - A/B Testing, Multi-model endpoints ****** NEW section Emerging AI Trends and Social Issues. How to detect a biased solution, ensure model fairness and prove the fairness ****** New Endpoint focused section on how to make SageMaker Endpoint Changes with Zero Downtime ****** Lab notebook now use spot-training as the default option. Save over 60% in training costs ****** NEW: Nuts and Bolts of Optimization, quizzes ****** All code examples and Labs were updated to use version 2.x of the SageMaker Python SDK ****** Anomaly Detection with Random Cut Forest - Learn the intuition behind anomaly detection using Random Cut Forest. With labs. ****** Bring Your Own Algorithm - We take a behind the scene look at the SageMaker Training and Hosting Infrastructure for your own algorithms. With Labs ****** Timed Practice Test and additional lectures for Exam Preparation added Welcome to AWS Machine Learning Specialty Course!I am Chandra Lingam, and I am your instructorIn this course, you will gain first-hand SageMaker experience with many hands-on labs that demonstrates specific conceptsWe start with how to set up your SageMaker environmentIf you are new to ML, you will learn how to handle mixed data types, missing data, and how to verify the quality of the modelThese topics are very important for an ML practitioner as well as for the certification examSageMaker uses containers to wrap your favorite algorithms and frameworks such as Pytorch, and TensorFlowThe advantage of a container-based approach is it provides a standard interface to build and deploy your modelsIt is also straightforward to convert your model into a production applicationIn a series of concise labs, you will in fact train, deploy, and invoke your first SageMaker modelLike any other software project, ML Solution also requires continuous improvementWe look at how to safely incorporate new changes in a production system, perform A/B testing, and even rollback changes when necessaryAll with zero downtime to your applicationWe then look at emerging social trends on the fairness of Machine learning and AI systems.What will you do if your users accuse your model as racially biased or gender-biased? How will you handle it?In this section, we look at the concept of fairness, how to explain a decision made by the model, different types of bias, and how to measure themWe then look at Cloud security – how to protect your data and model from unauthorized useYou will also learn about recommender systems to incorporate features such as movie and product recommendationThe algorithms that you learn in the course are state of the art, and tuning them for your dataset is especially challengingSo, we look at how to tune your model with automated toolsYou will gain experience in time series forecastingAnomaly detection and building custom deep learning modelsWith the knowledge, you gain here and the included high-quality practice exam, you will easily achieve the certification!And something unique that I offer my students is a weekly study group meeting to discuss and clarify any questionsI am looking forward to seeing you!Thank you!


Who this course is for:

• This course is designed for anyone who is interested in AWS cloud based machine learning and data science
• AWS Certified Machine Learning - Specialty Preparation