Relational Database and Normalization

1 hour

12 chapters

Beginner

This course delves into the theory behind relational databases. You'll learn what they are and see how they differ from non-relational databases. Throughout the course, we'll walk you through the ins and outs of database design and familiarize you with various types of relationships. Additionally, you'll explore the concepts of normalization and normal forms, equipping you with the knowledge to craft efficient and optimized databases.

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Ultimate Visualization with Python

3 hours

26 chapters

Intermediate

Data is everywhere around us and making sense of it is extremely important. Visulization helps us deal with data by finding certain patterns and insights in it. We will develop a solid foundation of data visualization using Python and its libraries, such as matplotlib and seaborn, to get as much information from data as possible in a neat and concise way. Without further ado, let's dive in!

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Detecting Patterns in Text with Regex

1 hour

8 chapters

Beginner

Unlock the power of regular expressions in Python with our comprehensive course designed for both beginners and experienced developers. This course will take you through the essential functions of the re module, including search, findall, finditer, and more, using practical examples and hands-on exercises. You'll learn how to extract and manipulate text data efficiently, enabling you to tackle complex string processing tasks with confidence. Whether you're looking to enhance your data analysis skills or streamline your coding workflow, this course provides the tools and knowledge to master regular expressions and elevate your programming capabilities.

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Time Series Essentials

1 hour

8 chapters

Intermediate

In this project, we are going to understand what a Time Series is and which are its main features.

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Web Scraping with Python

3 hours

23 chapters

Intermediate

Web Scraping is a process that can be used to automatically extract information from websites. This course will help you to get the data from sources for further manipulation and analysis!

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Structuring Applications Using OOP Principles

2 hours

16 chapters

Intermediate

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.

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Automating Data Collection from Web Sources

1 hour

7 chapters

Intermediate

In this project, we are going to understand how to create a simple web scraper in Python.

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Predicting Profitable Euro-Dollar Exchange Signals

3 hours

20 chapters

Advanced

In this course, we will examine the currency exchange rate relative to the euro. Our analysis will include Exploratory Data Analysis (EDA), generating visualizations, and developing a strategy to determine opportune moments for purchasing dollars. This strategy will involve trend detection techniques and constructing moving average curves to identify potential profit opportunities.

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Getting into NumPy Basics

1 hour

7 chapters

Intermediate

In this project, we will delve into the fundamentals of NumPy, exploring its core features and uncovering the reasons behind its significant impact on scientific computing. By understanding its architecture and capabilities, we will grasp why it is considered an essential tool for data scientists, researchers, and developers working in the realm of data analysis, machine learning, and beyond.

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Departments' Revenue Analysis

1 hour

7 chapters

Intermediate

We will use pandas to analyze departmental data by exploring, cleaning, and manipulating the dataset. Starting with basic inspection and data cleaning, we'll perform filtering, merge datasets, apply advanced filtering using multiple conditions, and finally group the data to extract meaningful insights.

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Linear Regression with Python

2 hours

19 chapters

Intermediate

Linear Regression is a crucial concept in predictive analytics. It is widely used by data scientists, data analytics, and statisticians as it is easy to build and interpret but powerful enough for many tasks.

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Excel Automation with Python

1 hour

11 chapters

Intermediate

In this project, we will study how to create, modify, and extract data from Excel spreadsheets using Python code.

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Data Anomaly Detection

3 hours

15 chapters

Advanced

Anomaly detection is integral to any data scientist's work: high-quality, cleaned, and well-prepared data is the key to success for almost any machine learning problem.

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Logistic Regression Mastering

1 hour

6 chapters

Advanced

Logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. In this project, we will leverage logistic regression to classify data into two distinct categories. The process will involve data preprocessing, model training, evaluation, and tuning to achieve optimal performance.

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Tableau Fundamentals

7 hours

76 chapters

Beginner

This corse provides a comprehensive introduction to Tableau's core features, empowering learners to create impactful data visualizations and dashboards. We will cover essential topics such as working with charts, filters, calculated fields, and parameters, as well as advanced techniques like combining data and creating interactive dashboards. By the end, you will have the skills to transform raw data into actionable insights with ease and confidence.

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