Course Code
intro2datascience
Duration
35 hours (usually 5 days including breaks)
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
Overview
This instructor-led, live training (onsite or remote) is aimed at professionals who wish to start a career in Data Science.
By the end of this training, participants will be able to:
- Install and configure Python and MySql.
- Understand what Data Science is and how it can add value to virtually any business.
- Learn the fundamentals of coding in Python
- Learn supervised and unsupervised Machine Learning techniques, and how to implement them and interpret the results.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
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
Testimonials
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Course Discounts
01/27/2020 - 09:30
Lisbon Airport Business Center
02/06/2020 - 09:30
Porto
02/10/2020 - 09:30
Lisbon Airport Business Center
02/11/2020 - 09:30
Porto
04/06/2020 - 09:30
Porto
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