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Discover the world of cloud computing by exploring its core technologies and practical applications in this course! Begin with the fundamentals of cloud computing and then focus on essential AWS services like S3 (Simple Storage Service) for scalable storage, EC2 (Elastic Compute Cloud) for virtual servers, and RDS (Relational Database Service) for managed databases. Gain hands-on experience as you learn how these services integrate to support modern applications efficiently.

A comprehensive, track designed for newcomers to Business Intelligence (BI). This interactive learning journey covers the essential tools and workflows of BI, including Python, SQL, and Tableau, through a mix of videos, practical tasks, and real-world projects. Learners will gain hands-on experience with each technology and build a full BI project from scratch, preparing them for entry-level roles in business intelligence and analytics.

This is a hands-on course that will help you understand the basics of object-oriented programming in Python. You will learn how to create classes, work with objects, use inheritance, and extend the capabilities of your programs.

Explore new concepts in C#. You'll go through a variety of topics and learn how to work with object-oriented programming and more advanced data structures. This will help you build more complex, well-structured applications and prepare you for the next step—working with .NET.

Kickstart your journey into Quality Assurance with essential skills in manual and automation testing. Learn the fundamentals of QA in web development, master HTML and JavaScript, explore data structures, and get introduced to automation testing to build a strong foundation for a career in QA.

Classify emails as spam or non-spam by analyzing the content of the emails. Preprocess the text data using techniques like tokenization and vectorization, and apply machine learning to build and evaluate a classification model. Develop a reliable tool for identifying spam emails.

Explore the essentials of GitHub, starting with understanding what GitHub is. Learn how to create your own repositories and manage remote branches. Discover how to sync changes across different environments. Dive into more advanced workflows, including pulling, pushing, and rebasing changes. Master the commands needed to efficiently collaborate with your team.

Explore the core techniques of unsupervised learning in Python. Master feature scaling, cluster analysis, dimensionality reduction, and anomaly detection to extract patterns, group data, and simplify complex datasets. Build practical skills for real-world, label-free data analysis.