Course Outline
Introduction to Data Science
- Defining Data Science.
- The Data Science Lifecycle.
- Tools and Methods in Data Science.
- Microsoft Azure Machine Learning.
Data Preparation
- Data Sources and Categories.
- Cleaning and Transforming Data.
- Feature Engineering.
Model Development and Training
- Supervised Learning Techniques.
- Unsupervised Learning Techniques.
- Choosing and Assessing Models.
- Understanding Model Outputs.
Model Deployment
- Deploying Models to Azure.
- Ensuring Scalability and Performance.
- Overseeing Deployed Models.
Assessing Model Performance
- Metrics for Model Evaluation.
- Optimizing Model Performance.
- Handling Model Versions.
Recap and Exam Readiness
- Revisiting Core Concepts.
- Strategies for Exam Preparation.
- Practical Exam Simulation.
Requirements
- A solid grasp of machine learning principles and practical experience with data analytics.
- Basic knowledge of programming and data manipulation is also advised.
Target Audience
- Data scientists.
- Data analysts.
- Individuals seeking to expand their machine learning knowledge and prepare for the DP-100 exam.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3900 € + VAT*
Contact us for an exact quote and to hear our latest promotions
Testimonials (3)
Learning that the QGIS and a tool that can used by other different professionals such land survey
Bame Duncan Koko - Bentel Technologies (Pty) Ltd
Course - QGIS for Geographic Information System
How to use open satellites data for real applications
Tshering Dorji - Druk Holding and Investments
Course - Advanced Geographic Information Systems (GIS)
Hands-on examples allowed us to get an actual feel for how the program works. Good explanations and integration of theoretical concepts and how they relate to practical applications.
