Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Data Science
- What is Data Science?
- The Data Science Process
- Data Science Tools and Techniques
- Microsoft Azure Machine Learning
Preparing Data
- Data Sources and Types
- Data Cleaning and Transformation
- Feature Engineering
Building and Training Models
- Supervised Learning
- Unsupervised Learning
- Model Selection and Evaluation
- Interpreting Model Outputs
Deploying Models
- Deploying Models to Azure
- Scalability and Performance
- Managing Deployed Models
Evaluating Model Performance
- Model Evaluation Metrics
- Tuning Model Performance
- Managing Model Versions
Summary and Exam Preparation
- Review of Key Concepts
- Exam Preparation Tips and Strategies
- Hands-on Practice Exam
Requirements
- A fundamental understanding of machine learning concepts and experience working with data analytics
- Familiarity with the basics of programming and data manipulation is also recommended
Audience
- Data scientists
- Data analysts
- Anyone who wants to learn about machine learning and prepare for the DP-100 exam
21 Hours
Testimonials (3)
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.
Ian - Archeoworks Inc.
Course - ArcGIS Fundamentals
All the topics which he covered including examples. And also explained how they are helpful in our daily job.
madduri madduri - Boskalis Singapore Pte Ltd
Course - QGIS for Geographic Information System
The thing I liked the most about the training was the organization and the location
