Description
AWS Certified Machine Learning Course – Specialization (Video Course). This course will help you succeed on the AWS Certified Machine Learning – Specialty exam by learning techniques and completing hands-on exercises. Earning the AWS Machine Learning Specialist certification will highlight your skills as a machine learning engineer. Typically machine learning engineers focus on data management and model building, but if you can also use cloud tools, you will be more valuable as an MLOps engineer. In this course, you will learn how to acquire data, go through the feature development process, train and evaluate models, and make them available for use by consumers. This course will show that you have complete machine learning development skills.
The instructor for this course, Milesia McGregor, will provide a combination of slides and hands-on demonstrations in AWS, as well as examples in Visual Studio with Python. This course is designed to help you pass the exam. This course includes an overview of concepts as well as hands-on practice using AWS tools such as Kinesis and EMR.
What you will learn:
- Effective Tips and Techniques for Passing the AWS Machine Learning Exam
- Familiarization and implementation of data ingestion solutions using Kinesis
- Evaluating Machine Learning Models
- Deploy Machine Learning Models Using AWS Tools
This course is suitable for people who:
- They are machine learning engineers.
- Development engineer (DevOps).
- My dream is to become a machine learning engineer.
Course Specifications AWS Certified Machine Learning Specialization (Video Course)
Course headings
Introduction
Lesson 1: Data Engineering
1.1 Creating data repositories for machine learning
1.2 Define and implement a data ingestion solution
1.3. Choosing between reception tools
1.4 Define and implement a data transformation solution
1.5 Practice: Questions and Exercises
Lesson 2: Exploratory Data Analysis
2.1 Cleaning and preparing data for modeling
2.2 Performing Function Engineering
2.3 Data analysis for machine learning
2.4 Data visualization for machine learning
2.5 Practice: Questions and Exercises
Lesson 3: Learning Models
3.1. Frame business problems as machine learning problems
3.2. Select the appropriate model for the machine learning task.
3.3 Understand the intuition behind the model
3.4 Training machine learning models
3.5 Select calculation option
3.6 Practice: Questions and Exercises
Lesson 4: Evaluating Models
4.1 Performing Hyperparameter Optimization
4.2. Use other hyperparameter optimization techniques.
4.3 Evaluating machine learning models
4.4. Comparison of models with different metrics
4.5 Implement machine learning best practices
4.6 Practice: Questions and Exercises
Lesson 5. Implementation and operation of machine learning
5.1 Building machine learning solutions for manufacturing
5.2 Problems of scaling the solution
5.3 Recommend and implement appropriate machine learning services
5.4 Applying AWS Security Core Practices to Machine Learning Solutions
5.5 Deployment and implementation of machine learning solutions
5.6 Practice: Questions and Exercises
Summary
Prerequisites for AWS Certified Machine Learning – Specialty (Video Course)
- Prerequisites: Knowledge of how to use various AWS tools to deploy ML models in various environments.
- Knowledge of data science, model training and evaluation principles.
course images
Example video course
installation instructions
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Subtitles: No
Quality: 720p
Download link
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size
356 MB