Python - Serie A
Embark on a journey of discovery with Python programming and Serie A data.
This micro course introduces you to data manipulation, visualization, and basic machine learning tailored for the tournament.
Explore player performance predictions, match outcome forecasts, and more.
By mastering Python, you'll equip yourself to unravel meaningful insights that influence game strategies and contribute to the rich tapestry of Serie A history
This micro course introduces you to data manipulation, visualization, and basic machine learning tailored for the tournament.
Explore player performance predictions, match outcome forecasts, and more.
By mastering Python, you'll equip yourself to unravel meaningful insights that influence game strategies and contribute to the rich tapestry of Serie A history
Python Bootcamp
Serie A Data Lab
The Intro course is free
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Video Introduction
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Paid Section Preview
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Theory
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Case Study Preview
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Exercises
#1 HEX Installation Guide
Sections included :
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The benefits of using HEX in Data Analysis
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HEX Sign Up guide with video and step by step instructions
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HEX Data Connect Data Guide with video and step by step instructions
#2 Introduction to Python
Introduction to Python
Python in the world of Sports Analytics
Terms you should know
HEX Installation Guide
Python Basics
Data Types
Python Input
Python Output
Python Mathematics
Python Mathematic Operations
Python Strings
Escape Characters
Casting
Practical Examples
Quiz
Python in the world of Sports Analytics
Terms you should know
HEX Installation Guide
Python Basics
Data Types
Python Input
Python Output
Python Mathematics
Python Mathematic Operations
Python Strings
Escape Characters
Casting
Practical Examples
Quiz
#3 Python Data Structures
Python Data Structures
Python Lists
Python Tuples
Python Sets
Python Dictionaries
Practical Examples
Quiz
Python Lists
Python Tuples
Python Sets
Python Dictionaries
Practical Examples
Quiz
#4 Python Functions
Python Functions
Defining & Calling a Function
Function Arguements
Return Values
Scope of Variables
Lambda Functions
Built-in Functions
Practical Examples
Quiz
Coding Assessment
Defining & Calling a Function
Function Arguements
Return Values
Scope of Variables
Lambda Functions
Built-in Functions
Practical Examples
Quiz
Coding Assessment
#5 Python Modules
Python Modules
random - Module
math - Module
Python Counter
Practical Examples
Quiz
random - Module
math - Module
Python Counter
Practical Examples
Quiz
#6 Python Conditionals
Python Conditionals
Comparison Operators
Logical Operators
Conditional Statements
Practical Examples
Quiz
Coding Assessment
Comparison Operators
Logical Operators
Conditional Statements
Practical Examples
Quiz
Coding Assessment
#7 Python Loops
For Loops
While Loops
For vs While Loops
While & For Loops in Conjunction
Quiz
Coding Assessment on For Loops
Coding Assessment on While Loops
While Loops
For vs While Loops
While & For Loops in Conjunction
Quiz
Coding Assessment on For Loops
Coding Assessment on While Loops
#8 Python Regular Expressions
Python Regular Expressions
re.search() Function
re.match() Function
re.findall() Function
re.finditer() Function
re.sub() Function
re.split() Function
Practical Examples
Quiz
Coding Assessment
re.search() Function
re.match() Function
re.findall() Function
re.finditer() Function
re.sub() Function
re.split() Function
Practical Examples
Quiz
Coding Assessment
#9 Overall Python Assignment
Coding Assessment
#10 Optional Content - Practicing with Python Locally
Local Python Installation
PyCharm Installation
PyCharm Installation
Part 2 - Python for Data Analytics
The Intro Course is Free
Elevate your knowledge and sharpen your insights with our specially curated Case Studies! Dive deep into the league of your preference and uncover strategies, trends, and data-driven techniques that will propel you to the next level!
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Video Introduction
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Paid Section Preview
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Theory
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Case Study Preview
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Exercises
Fully Interactive
#2 Introduction to Python Data Analysis & Numpy
Introduction to Python Sports Data Analysis
NumPy - Arrays
NumPy - Indexing and Slicing
NumPy - Broadcasting
NumPy - Mathematical Functions
NumPy - Linear Algebra
Quiz
NumPy - Arrays
NumPy - Indexing and Slicing
NumPy - Broadcasting
NumPy - Mathematical Functions
NumPy - Linear Algebra
Quiz
#3 Pandas
Introduction to Pandas
Pandas Series
Pandas DataFrames
Data Inspection and Exploration
Data Cleaning
Handling Missing Values
Removing Duplicates
Sorting & Ranking Data
Applying Functions
Grouping Data
Merging Joining & Reshaping
Data Grouping & Aggregation
Timeseries Data
Categorical Data
Practical Examples
Quiz
Coding Assessment
Pandas Series
Pandas DataFrames
Data Inspection and Exploration
Data Cleaning
Handling Missing Values
Removing Duplicates
Sorting & Ranking Data
Applying Functions
Grouping Data
Merging Joining & Reshaping
Data Grouping & Aggregation
Timeseries Data
Categorical Data
Practical Examples
Quiz
Coding Assessment
#4 Matplotlib
Basics of Matplotlib
Line Plots
Scatter Plots
Bar Plots
Pie Plots
Titles, Labels & Legends
Colors, Markers & Line Styles
Ticks, Tick, Labels & Limits
Histograms and Box Plots
Heatmaps and Contour Plots
3D Plots
Plot Style & Customization
Grid and Plot Layout
Subplots, Sharing Axes & Spacing
Pandas & Matplotlib
Practical Examples
Quiz
Line Plots
Scatter Plots
Bar Plots
Pie Plots
Titles, Labels & Legends
Colors, Markers & Line Styles
Ticks, Tick, Labels & Limits
Histograms and Box Plots
Heatmaps and Contour Plots
3D Plots
Plot Style & Customization
Grid and Plot Layout
Subplots, Sharing Axes & Spacing
Pandas & Matplotlib
Practical Examples
Quiz
#5 Seaborn
Basics of Seaborn
Basic Plotting
Box, Violin & Swarm Plots
FacetGrids, PairGrids and more
Heatmaps and Clustermaps
Regression and Line Plots
Practical Examples
Quiz
Basic Plotting
Box, Violin & Swarm Plots
FacetGrids, PairGrids and more
Heatmaps and Clustermaps
Regression and Line Plots
Practical Examples
Quiz
#6 Plotly
Basics of Plotly
Graph Objects & Express
Line, Bar & Pie Charts
Histograms and Box Plots
Scatter Plots and Bubble Charts
Heatmaps
Geographic Plots
Interactivity
Practical Examples
Quiz
Graph Objects & Express
Line, Bar & Pie Charts
Histograms and Box Plots
Scatter Plots and Bubble Charts
Heatmaps
Geographic Plots
Interactivity
Practical Examples
Quiz
#7 SciPy
Data Manipulation with Scipy
Basics of Statistical Analysis
Hypothesis Testing
Types of t-tests
Analysis of Variance
Linear Algebra
SciPy Matrix Operations
Eigenvalues and Eigenvectors
Linear Equations
Optimization
Advanced Aspects of SciPy
Interpolation
Integration
Fourier Transform
Spatial Data and Distance
Basics of Statistical Analysis
Hypothesis Testing
Types of t-tests
Analysis of Variance
Linear Algebra
SciPy Matrix Operations
Eigenvalues and Eigenvectors
Linear Equations
Optimization
Advanced Aspects of SciPy
Interpolation
Integration
Fourier Transform
Spatial Data and Distance
Data Labs
#8 Case Studies
A Data Lab is essentially a dynamic learning environment where we put into practice the latest skills we've acquired in Python through the League of your choosing.
In this section, our focus shifts to the realm of Serie A data.
Data Lab serves as a practical course where we immerse ourselves in hands-on Case Studies, applying our knowledge to gain insights and make data-driven decisions.
With each Case Study, we explore new dimensions of data analysis, allowing us to delve into the latest trends and uncover hidden patterns within the world of Serie A data.
In this section, our focus shifts to the realm of Serie A data.
Data Lab serves as a practical course where we immerse ourselves in hands-on Case Studies, applying our knowledge to gain insights and make data-driven decisions.
With each Case Study, we explore new dimensions of data analysis, allowing us to delve into the latest trends and uncover hidden patterns within the world of Serie A data.
Case Study #1: Fiorentina Performance
In this Python Data case study, we embark on an exciting journey through Serie A 2023, where we explore and analyze the performances Fiorentina over the season.
Join us as we dive into the world of football data, using Python queries to unravel the secrets behind each team's success. 🔍
Case Study #2: Lazio vs Roma
📊📈🔍 In this case study, we'll use data analysis tools to explore the Lazio vs Roma football match.
Discover team strategies, individual performances, positional influences, and match dynamics, as we delve into the treasure trove of raw data! 🧠💻⚽🔥
Case Study #3: Goal-Scoring Patterns
In this case study, we thoroughly investigate a detailed dataset reflecting the goals scored in the "Juventus vs Napoli" match of Serie A 2023. Leveraging Python's powerful data analysis libraries, we formulate probing queries to expose critical insights about the goal-scoring trends and their implications within the match.
Through our analysis, we aim to answer questions concerning goal distribution, types of goals, decisive goal scorers, and more. This exploration empowers us to achieve a comprehensive understanding of the intricate dynamics behind the goals scored in this highly competitive match. 📈
Case Study #4: Defensive Performance
The Serie a is recognized for featuring some of the most thrilling offensive prowess in global football. Yet, behind each triumphant team stands a robust defensive backbone.
In this Python data case study, we turn our attention to the defensive aspect of the game, diving into the dataset to investigate and analyze defensive performance in the Premier League.
Using Python's powerful data analysis tools, we'll transform raw data into comprehensive insights. 🔍
Case Study #5: Offensive Performance
Offensive Performance represent some of the most electrifying moments in football, with team fortunes often hanging in the balance.
In this Python-based case study, we dive into the penalty shootout data from Serie A, striving to unearth trends and insights related to these tense circumstances.
By evaluating aspects such as success rates, goalkeeper performances, and the influence of the penalty shootout sequence, we aim to achieve an enriched understanding of the dynamics of penalty shootouts in one of the world's most prestigious football tournaments. 🐍🔍
Case Study #6: Season Performance
In our case study today, we don the hat of a football analyst for one of the most successful teams in recent years, Lazio. As part of this journey, we will utilize Python, one of the most versatile programming languages in the world, to conduct an in-depth analysis of Lazio's performance in the 2022-2023 La Liga season.
We will do this through a combination of data exploration, visualization using the interactive plotting library - Plotly, and statistical analysis using Scipy.
Case Study #7: Player Season Performance
🌟🎉 Ladies and gentlemen! Welcome to a deep dive into the world of football statistics and data analytics. Today, we will be exploring the performance of one of the most spectacular football players in the world, Di Maria of Benfica, in the Serie A 2022-2023 season. ⚽🏆
Maria, a truly versatile forward and Benfica's talisman, has mesmerized fans all over the globe with his scintillating performances. As data analysts, we have the privilege of understanding and illustrating his magic in numbers and plots. 📊📈
#9 Optional Content - Practicing with Python Locally
Local Python Installation
PyCharm Installation
PyCharm Installation
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