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.

Data is everywhere around us, and making sense of it is extremely important. Visualization helps you deal with data by finding certain patterns and insights in it. You 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.

"Databases in Python" is a hands-on course designed to teach you the fundamentals of working with databases using Python, focusing on the sqlite3 library and SQLAlchemy. You’ll learn how to store, modify, and retrieve data, build efficient queries, and configure databases for your projects. The course covers both SQL basics and the ORM (Object-Relational Mapping) approach, which allows you to interact with databases through Python objects. This course is perfect for beginners looking to deepen their skills in data management, application development, and information handling.

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.

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.

Learn to extract valuable data from websites automatically. Master techniques to gather information efficiently, enabling you to perform in-depth analysis, make data-driven decisions, and unlock new insights from the vast ocean of online information.

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.

Dive deep into the world of TensorFlow with our course, designed to give you a robust understanding of its core components. Begin with an exploration of tensors and the basics of TensorFlow framework. By the course's end, you'll have honed the skills to build tensor-driven systems, including crafting a basic neural network. Equip yourself with the knowledge to harness TensorFlow's full potential and set the foundation for advanced deep learning pursuits.

Learn how to write faster and more memory-efficient code by mastering performance measurement, selecting the right data structures, and leveraging built-in tools. We'll focus on practical optimization techniques for handling large datasets, efficient string operations, and partial sorting, ensuring your code is both robust and scalable.

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.

This course gives you a basic knowledge of statistics. It is intended for students with basic knowledge of Python syntax as they will be working with NumPy and pandas modules. During the course, you will become familiar with the basic concepts and then gradually move on to more complex concepts and tasks.

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.

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.

In machine learning, classification is used in predictive modeling to assign input data with a class label. Sounds difficult? Don't worry! Let's cope with this! Welcome to the ML!

Gain a solid understanding of cluster analysis, a key unsupervised learning technique for uncovering patterns in unlabeled data. Explore the essentials of K-Means, Hierarchical Clustering, DBSCAN, and GMMs, and get hands-on experience with real datasets to build confidence in applying clustering to real-world problems.