AutoML Courses
AutoML Courses
July 13, 2024 Comments Off on AutoML CoursesAutoML Courses
AutoML Training Courses
All in all AutoML (Automated Machine Learning) helps organizations deploy Machine Learning (ML) models faster, by making the ML pipeline process more efficient and less error-prone. If you’re getting started with AutoML, this article will take you through the first steps you need to find a tool and get started.
- Google Cloud AutoML Training Course.
- AutoML with Auto-Keras Training Course.
- AutoML with Auto-sklearn Training Course.
- H2O AutoML Training Course.
- PGC AIML – Machine Learning.
- PGC AIML – Deep Learning with Keras and TensorFlow.
Why Learn AutoML?
Overall Automated machine learning is the process of automating the tasks of applying machine learning to real-world problems. AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment.
Part-Time
Fast forward your career in the IT industry with a part-time course at School of IT. In turn Part-time courses allow working professionals to transition into a new skill set while working. Moreover at School of IT we are agile and customize a course to the individual.
Full Time
Ready to start a career in IT? Use the data modelling as a full time student at School of IT.
High School
Learn about the AutoML software and prepare for the future while you’re still in high school. Thus no matter where you are, we come to you! Thus giving you the analytical skills to pursue your dreams!
Corporate
Learn about automating the tasks of applying machine learning to real-world problems and up skill yourself or your company while you’re working. Thus no matter where you are, we come to you and give the tools to move up in your company.
By the end of the Google Cloud AutoML Training Course, students will have usable knowledge of the following:
Course Outline
- Google’s ML ecosystem
- AutoML line of products
- Applications for AutoML products
- Challenges and limitations
- Preparing datasets
- Creating and deploying models
- Text and document training (classification, extraction, analysis)
- Labeling images
- Training and evaluating models
- AutoML Vision Edge
- Preparing datasets (source and target language)
- Creating and managing models
- Testing models
- Analyzing documents
- Image prediction
- Translating content
- AutoML Tables for structured data
- AutoML Video Intelligence for videos
By the end of the AutoML with Auto-Keras Training Course, students will have usable knowledge of the following:
Course Outline
- Introduction
- Setting up a Working Environment
- Installing Auto-Keras
- Anatomy of a Standard Machine Learning Workflow
- How Auto-Keras Automates the Machine Learning Workflow
- Searching for the Best Neural Network Architecture with NAS (Neural Architecture Search)
- Case Study: AutoML with Auto-Keras
- Downloading a Dataset
- Building a Machine Learning Model
- Training and Testing the Model
- Tuning the Hyperparameters
- Building, Training, and Testing Additional Models
- Tweaking the Hyperparameters to Improve Accuracy
- Configuring Auto-Keras for Deep Learning Models
- Troubleshooting
By the end of the AutoML with Auto-sklearn Training Course, students will have usable knowledge of the following:
Course Outline
- Introduction
- Setting up a Working Environment
- Installing Auto-sklearn
- Anatomy of a Standard Machine Learning Workflow
- How Auto-sklearn Automates the Machine Learning Workflow
- Searching for the Best Neural Network Architecture with NAS (Neural Architecture Search)
- Case Study: AutoML with Auto-sklearn
- Downloading a Dataset
- Building a Machine Learning Model
- Training and Testing the Model
- Tuning the Hyperparameters
- Building, Training, and Testing Additional Models
- Tweaking the Hyperparameters to Improve Accuracy
- Configuring Auto-sklearn for Deep Learning Models
- Troubleshooting
By the end of the H2o AutoML Training Course, students will have usable knowledge of the following:
Course Outline
- Introduction
- Setting up a Working Environment
- Installing H2O
- Anatomy of a Standard Machine Learning Workflow
- Data-preprocessing, feature engineering, deployment, etc.
- Statistical and Machine Learning Algorithms
- Gradient boosted machines, generalized linear models, deep learning, etc.
- How H2O Automates the Machine Learning Workflow
- Binary Classification, Regression, etc.
- Case Study: Predicting Product Availability
- Downloading a Dataset
- Building a Machine Learning Model
- Specify a Training Frame
- Training and Cross-Validating Different Models
- Tuning the Hyperparameters
- Training two Stacked Ensemble Models
- Generating a Leaderboard of the Best Models
- Inspecting the Ensemble Composition
- Training many Deep Neural Network Models
- Troubleshooting
- Google Cloud AutoML Training Course price is R18 900 for 10 hours.
- AutoML with Auto-Keras Training Course price is R18 900 for 10 hours.
- AutoML with Auto-sklearn Training Course price is R18 900 for 10 hours.
- H2O AutoML Training Course price is R18 900 for 10 hours.
Prerequisites
Experience with data analytics Familiarity with machine learningWho Should Attend this AutoML Training Course?
Overall Audience: AutoML makes machine learning more accessible, allowing individuals that have a relatively limited level of experience to build working models. However, experienced engineers can also benefit from auto ML, enabling them to work quickly and reallocate their time to explore new opportunities.What's included in this AutoML Training Course?:
Courseware- Ebooks
- Professional notes
- International exam resources and how to book the international exam/s.
- Interactive software
- Proposed Schedule
The career prospects for AI and Machine Learning is high in demand. Data Science careers are everywhere.
- All in all a Data Architect
- Data Scientist.
- Data Analyst.
- AI Specialist.