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
Day 1
- Data Science: an overview
- Practical part: Let’s get started with Python - Basic features of the language
- The data science life cycle - part 1
- Practical part: Working with structured data - the Pandas library
Day 2
- The data science life cycle - part 2
- Practical part: dealing with real data
- Data visualisation
- Practical part: the Matplotlib library
Day 3
- SQL - part 1
- Practical part: Creating a MySql database with tables, inserting data and performing simple queries
- SQL part 2
- Practical part: Integrating MySql and Python
Day 4
- Supervised learning part 1
- Practical part: regression
- Supervised learning part 2
- Practical part: classification
Day 5
- Supervised learning part 3
- Practical part: building a spam filter
- Unsupervised learning
- Practical part: Clustering images with k-means
Requirements
- An understanding of mathematics and statistics.
- Some programming experience, preferably in Python.
Audience
- Professionals interested in making a career change
- People curious about Data Science and Data Analytics
35 Hours
Testimonials (1)
Course with practical knowledge. The first time I participated in a one-on-one training session, which significantly facilitated communication and knowledge acquisition. A big advantage here as well.
Mateusz Macalik - LG Energy Solution Wroclaw Sp. z o.o.
Course - Introduction to Data Science
Machine Translated
