
Learn to create and use dictionaries in Python, access values by keys, and iterate with .keys and .values. Practice adding, deleting, and checking membership with country city mappings.
Learn to identify and handle python exceptions, including name error, index error, and zero division error, using try-except and else blocks with practical examples.
Learn how to use built-in and user defined functions in python. Define functions with def, pass arguments, and return results such as length and basic calculations.
Create a NumPy array by importing numpy as np, define an array with values zero to four, and access the third element (index two) by printing it.
Learn to create numpy arrays, perform elementwise addition and multiplication, compute the dot product, and use numpy pi and sign to evaluate functions.
Apply logistic regression, a supervised learning technique, to predict if a rookie lasts more than five years in NBA dataset, using data cleaning, imputing nulls with mean, and train-test split.
Welcome to the Sports Analytics in Python course on Udemy! In this course, you will learn how to apply the power of Python programming to sports analytics.
Sports analytics has become an increasingly important field in recent years, as teams, athletes, and analysts seek to gain a competitive edge through data-driven insights. In this course, you will learn how to use Python programming to explore and analyze sports data, including data on athlete performance, team statistics, and league trends.
Throughout the course, you will work on a series of hands-on projects, starting with the basics of Python programming and data analysis, and gradually building up to more advanced techniques. You will learn how to clean and manipulate data, visualize data using Python's powerful data visualization libraries, and perform statistical analysis on sports data.
By the end of the course, you will have gained a solid foundation in Python programming and sports analytics, and you will be able to apply your new skills to a wide range of real-world problems. Whether you are a sports enthusiast, a data analyst, or simply looking to expand your programming skills, this course is designed to help you achieve your goals.
Join us today and discover the power of Python programming for sports analytics!