Telco Cloud Data-Science for Beginners
This training provides a practical introduction to Data Science and machine learning, covering Python basics, data manipulation, visualization, statistical analysis, and core modeling techniques such as regression, classification, and clustering. Through hands-on labs, participants build a solid understanding of the end-to-end data workflow and how to apply data science methods to real-world use cases.
.svg){kind=small}
About The Lab
Prerequisites
Audiences
Lab Architecture
This hands-on lab introduces Data Science through a practical, beginner-friendly environment. It covers the core workflow of collecting, cleaning, exploring, and analyzing data using Python, Pandas, and basic visualization tools. Learners work with real datasets, build simple models, and understand how data can be used to extract insights, support decisions, and prepare for more advanced AI and machine learning topics.
Why this Lab ?
This training covers the core concepts and practical techniques of Data Science and machine learning. Participants will learn Python fundamentals, data manipulation, visualization, statistical analysis, and key modeling approaches such as regression, classification, and clustering. Through hands-on labs, the course provides a strong foundation to understand the complete data workflow and apply data science techniques to real-world problems.
Lab Objectives
- Understand Python fundamentals and how to use Jupyter Notebook for data analysis.
- Work with datasets using NumPy and Pandas for data manipulation.
- Create data visualizations with Seaborn to explore and understand data.
- Train and evaluate a basic machine learning model using Logistic Regression.
- Apply data science techniques such as clustering with K-Means and basic sentiment analysis on text data.
