Introduction to SQL

4 hours

41 chapters

This course is for you if you are new to SQL, you want to quickly learn how to get the most out of SQL and you want to learn how to use SQL in your own application development.

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Pandas First Steps

4 hours

34 chapters

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.

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Exploratory Data Analysis of Nobel Prizes

1 hour

6 chapters

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.

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Text Summarization with TF-ISF

2 hours

12 chapters

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.

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NumPy in a Nutshell

3 hours

21 chapters

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.

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Recognizing Handwritten Digits

2 hours

10 chapters

In this project, our primary objective will be to delve into the identification of handwritten digits through the application of machine learning algorithms. This endeavor aims to harness the power of machine learning to effectively interpret and understand handwritten digits, showcasing the potential of these algorithms in processing and analyzing complex visual information.

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Advanced Techniques in pandas

4 hours

33 chapters

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.

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Introduction to Neural Networks

3 hours

19 chapters

Neural networks are powerful algorithms inspired by the structure of the human brain that are used to solve complex machine learning problems. You will build your own Neural Network from scratch to understand how it works. After this course, you will be able to create neural networks for solving classification and regression problems using the scikit-learn library.

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Natural Language Handling

1 hour

11 chapters

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.

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ML Introduction with scikit-learn

4 hours

33 chapters

Machine Learning is now used everywhere. Want to learn it yourself? This course is an introduction to the world of Machine learning for you to learn basic concepts, work with Scikit-learn – the most popular library for ML and build your first Machine Learning project. This course is intended for students with a basic knowledge of Python, Pandas, and Numpy.

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Ultimate Visualization with Python

3 hours

26 chapters

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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Introduction to NLP

4 hours

24 chapters

Let's explore the fundamentals of Natural Language Processing (NLP) as you delve into text preprocessing techniques and various text models used to represent text data. You will gain practical insights and hands-on experience with the tools and methods essential for analyzing and interpreting textual data effectively. This course equips you with the skills to transform raw text into meaningful information, paving the way for advanced applications in AI and machine learning.

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Association Rule Mining

2 hours

15 chapters

The Association Rule Mining course offers a comprehensive exploration of the principles and methodologies behind uncovering meaningful associations in large datasets. From understanding the fundamental measures like support, confidence, and lift to employing advanced algorithms such as Apriori and FP-Growth, you will develop the skills necessary to extract valuable insights from transactional data. Through practical applications in diverse domains like retail, healthcare, and finance, participants learn to drive data-driven decision-making, optimize business processes, and uncover hidden opportunities for growth and innovation.

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Time Series Essentials

1 hour

8 chapters

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

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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