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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.

Python is a high-level, interpreted, general-purpose programming language. Distinguished from languages such as HTML, CSS, and JavaScript, which are mainly utilized in web development, Python boasts versatility across multiple domains, including software development, data science, and back-end development. This course will guide you through Python's fundamental concepts, equipping you with the skills to create your own functions by the conclusion of the program.

Build a content-based recommendation engine for anime using pandas and scikit-learn, focusing on feature engineering, EDA for hidden gems, similarity-based recommendations, and insightful visualizations – all without defining custom functions.

After completing this track, you will be able to write basic Python code, understand its syntax, and set up a Python development environment. You'll have the skills to start your programming journey and build a strong foundation for further learning.

Explore the essentials of Python's core data structures: lists, dictionaries, tuples, and sets. Learn to create, index, modify, and combine these collections using built-in methods such as append(), pop(), and update(), building a solid foundation for organizing and manipulating data in your programs.

A hands-on, notebook-style case study guiding you through the process of forecasting smart home energy consumption using regression and time series feature engineering. You will work step-by-step with pandas, seaborn, matplotlib, and scikit-learn, focusing on direct, linear code execution without function definitions.

A practical, beginner-friendly track that takes learners from writing their first Python code to building and evaluating their first machine learning model for data science. This track emphasizes hands-on coding, real-world data manipulation, and actionable insights using Python and essential data science libraries.

A practical introduction to Databricks, its core concepts, and hands-on data manipulation using Python and SQL. This course is designed for absolute beginners, focusing on clarity, simplicity, and real-world application.