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 (5)
The trainer adapted the materials and contents to what he thought would be best for us and he succeeded. The quality of the training was excellent.
Jorge Sanchez Hernandez - CSMART - Carnival
Course - QGIS for Geographic Information System
A lot of patience
Mateusz - WestWind Energy Polska Sp. z o.o.
Machine Translated
Professional and very practical, usuefull in a daily work
Jozefin Rékasi - SC Automobile Dacia SA
Course - Advanced Data Analysis with TIBCO Spotfire
It covered the areas i said i was interested in before the course: data relationships, using python script. Connecting to databases will be covered in the advanced module.
Cristian Tudose - SC Automobile Dacia SA
Course - Introduction to Spotfire
I genuinely enjoyed the lots of labs and practices.
