Download Udemy – Learning Predictive Analytics with Python 2023-3

Description

Learning Predictive Analytics with Python course. Predictive analytics is a branch of advanced analytics that uses statistical techniques, machine learning algorithms, and data mining to analyze historical data and predict future events or trends. It helps organizations identify patterns, understand trends and predict outcomes, which can lead to better decision making and more efficient operations. Predictive analytics is used in a variety of industries, including finance, healthcare, marketing, and manufacturing. Using predictive analytics, organizations can gain insights into customer behavior, optimize marketing campaigns, detect fraud, and improve supply chain management, among other benefits. In this course, we’ll cover all the important basics of predictive analytics and then start with all the important concepts about Python and object-oriented programming. Python is a general-purpose language used in major fields such as data science, machine learning, and web development. This course covers almost all the fundamental concepts of Python. As a beginner, it is essential to have a clear and thorough initial understanding of the concepts. This course focuses on these points and we have tried our best to present it in a way that will help you clear the basics as well as the concepts. The key concepts covered in this course are:

1. Internal data types such as list, dictionary, tuple, collection, string with their capabilities.

2. Understanding list, lambda function and decorations in Python

3. Object-oriented programming in Python

4. Creating an application using all the concepts learned

5. Predictive analysis

6. A prediction model using random forest algorithm to predict the winner between two given Pokemon.

Does this course cover all data science and web development concepts? I’ll be honest with you, this course doesn’t cover all web development concepts (although we have different courses for that which we’ll discuss another day), however, it does cover the fundamentals of data science and machine learning. Gives.