Applied Data Science Course (online)
Group | Online Sessions (GMT) | Duration | Registration |
---|---|---|---|
A |
Mondays 14h00 to 18h00 (GMT) |
36 Hours |
Available Seats: 30
Registration Deadline
REGISTER NOW
31/05/2024 23:59 |
Description
This is a project-based course designed for trainees with some programming background interested to learn machine learning techniques and predictive analytics. As a programming language, we will Python to develop the machine learning algorithms. This course is certified by EIT Tech Talent, European Union.
COURSE OBJECTIVES
On successful completion of this course, students will be able to:
- Understand and describe the essential concepts of AI and Machine Learning
- Identify and implement appropriate Machine Learning techniques to build and validate the predictive models
- Clean the datasets and prepare them for machine Learning projects
- Understand and implement the supervised and un-supervised machine learning algorithms
- Practically design and run the Machine Learning projects in Python
- Practice all the techniques they learned through a final project applied to real-world datasets.
COURSE SYLLABUS
- Introduction to Data Science: Concepts and Applications
- Fundamentals of Machine Learning
- Machine Learning pipeline
- Data Preparation Techniques
- Feature Engineering Techniques
- How to manage a data science project
- How to design a machine learning project
- Train and Test Datasets
- Data preprocessing, Cleaning, and visualization
- Supervised and unsupervised algorithms
- Building and validating the Regression models
- Building and validating the Decision Trees
- Building Clustering and Classification Models
- Tuning the machine learning models
- Final Project: Applying Machine Learning techniques to real datasets and building the predictive models