Practical Machine Learning
This 5-day course is designed for people who are already working on basic data science problems and starting the statistical analysis of data with python. By attending this course you’ll learn what an effective Machine Learning approach looks like in an organisation. You’ll learn how to implement different Machine learning models, validate their quality and how to implement them practically.
Kirjeldus
Target audience: This course is aimed at fledgling data scientists and analysts who wish to gain more in-depth knowledge of Machine Learning.
Sihtgrupp
GCSE Mathematics or above. Must be comfortable with analytical and mathematical thinking. Familiar with basic python programming: variables, control flow, scope, data structures and functions. Must be comfortable with algorithmic thinking. Familiar with basics of data analysis including databases, descriptive statistics, and typical business use cases.
Programm
- Introduction to Data Science
- Python for Data Science
- Fundamentals of Statistics
- Exploratory Data Analysis
- Data Preparation
- Choosing ML Algorithms
- Building ML Models
- Evaluating ML algorithms and Model Selection
- Deploying ML Models
Omandatavad oskused
- explore and prepare data;
- develop ML models;
- how to pick ML algorithms for a given task;
- understand techniques and metrics used to determine the quality of ML models.
Eeldused
Participation requirements
Lisainfo
The training is held in cooperation with our partner QA.
Investeering
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