In the world of business, making decisions based on hard data rather than intuition can be the key to success. This course focuses on one crucial technique: analyzing A/B test data. 

The centerpiece of the course is a project where you'll conduct a detailed analysis of an A/B test. This project, which you can showcase in your CV, is hosted on Codefinity, allowing you to continually refine it and demonstrate your growing expertise.

Embark on our comprehensive Python course tailored to mastering A/B testing, a vital technique in data-driven decision making. This course will guide you through using essential Python libraries such as Pandas for data manipulation, NumPy for numerical analysis, and SciPy for advanced statistical calculations. Learn to create insightful visualizations with Matplotlib. By the end of the course, you'll be equipped to perform robust A/B testing on real-life data, ensuring you can make informed decisions that impact key business outcomes.

We will delve into the concept of Exploratory Data Analysis (EDA) and explore its critical role within every Data Analysis process, particularly focusing on the analysis of Nobel Prizes. EDA serves as a foundational step that enables data scientists and analysts to uncover patterns, anomalies, and insights from data through visual and statistical methods.

Pandas is an extremely user-friendly library for data analysis. It's also designed to handle large datasets, using data structures like DataFrame and Series. This makes it an invaluable tool for Data Science. In this guide, you'll get acquainted with a range of statistical functions, including how to find correlations, modes, medians, and maximum and minimum values within a dataset. You'll also learn how to handle missing values and manipulate specific values, as well as how to remove them.

This course is perfect for those who already have a basic understanding of SQL and want to delve into more advanced concepts to craft more powerful queries. Throughout the course, you will become familiar with data grouping and filtering grouped data. You will also learn how to work with multiple tables simultaneously, including how to combine them. Additionally, you will explore different types of table joins and how to apply them in practice.

In this project, we aim to design and implement a text summarizer utilizing the Python programming language as our foundational tool. To achieve this, we will be leveraging the powerful Natural Language Toolkit which is instrumental in the processing and analysis of textual data.

NumPy is one of the basic packages for scientific computing in Python. The 'NumPy in a Nutshell' course will introduce you to such a powerful tool as NumPy, which is convenient for working with arrays of different sizes. After completing this course, you will be able to easily work with matrices, using various functions. In addition, during the course, you will learn basic methods for working with arrays that simplify code writing.

In this project, we will be utilizing the capabilities of the Natural Language Toolkit (NLTK), a versatile and comprehensive library in Python designed for working with human language data. Our focus will encompass several core areas of natural language processing: tokenization, stemming, tagging and parsing. These NLTK features will form the backbone of our text processing and analysis tasks, making it an essential tool in our project for handling and extracting meaningful insights from language data.

Navigating the intricacies of Business Analysis is a transformative journey that unveils the dynamic intersection of strategy, technology, and organizational objectives. Delve into the heart of this discipline, where professionals craft solutions, facilitate change and bridge the gap between business needs and IT capabilities.

Unlock the full potential of Python's most essential library for numerical computing, NumPy. This comprehensive course is designed to take you from a beginner's understanding to an advanced level of proficiency in NumPy. Whether you're a data scientist, engineer, researcher, or developer, mastering NumPy is essential for efficient data manipulation, scientific computing, and machine learning.

This course contains a lot of useful functions for a future data analyst. You will learn different ways of extracting data and even set conditions on it. After it, you will be familiar with the methods of grouping data. Also, you will learn how to preprocess data. Each section has its data set so that the course will be gripping.

Python provides three ways for executing the loops. While all the ways provide similar basic functionality, they differ in their syntax and condition checking time. Today we start learning these loops. Welcome to Python Loops Tutorial!

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

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 visulization 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!