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What you’ll learn

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Uncover the basics of Data Science & it’s applications

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Master Python programming fundamentals for data analysis

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Dive into key libraries like NumPy & Pandas for Data manipulation

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Explore Data visualization techniques using Matplotlib and Seaborn

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Understand the principles of Modeling & Machine learning in Data science

Unleash the Power of Data Science Foundations.

Join today to build a strong foundation in data science with Python!

Feeling overwhelmed by

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The complexity of Python syntax and programming concepts

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The challenge of learning NumPy and Pandas for data manipulation

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The need to create impactful data visualizations

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The multitude of tools and libraries in data science

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Getting started with predictive machine learning models

Unlock the Power of Data Science Foundations

Explore and understand the core concepts of data science:

Dive into Python essentials for effective data manipulation and analysis.

Master NumPy and Pandas libraries for array operations, data cleaning, and manipulation.

Learn data wrangling techniques and gain insights from real-world case studies.

Enhance your data visualization skills using Matplotlib, Seaborn, and Plotly.

Understand the fundamentals of modeling, clustering, and regression techniques.

Explore the application of machine learning in sports analytics and decision-making.

meet your data science coach

Evan Callaghan

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Passionate about the intersection of data science and sports analytics.

Currently pursuing my Master of Science in Statistics at Queen’s University, I am deeply passionate about the intersection of data science and sports analytics. My thesis work revolves around time-series data imputation using cutting-edge machine learning techniques, aiming to enhance data quality and insights.


During my undergraduate studies, I pursued applied math, computer science, and data analytics while also competing as a collegiate golfer. This unique blend of academic rigor and practical experience has equipped me with a comprehensive understanding of data science principles and their real-world applications, especially in the sports domain.

I am eager to share my knowledge and insights with you in FoundationZ of Data Science, where we'll explore the foundational concepts of Python programming, data manipulation with NumPy and Pandas, advanced data visualization, modeling techniques, and the application of machine learning in sports analytics. Join me on this exciting journey to unlock the power of data science and elevate your skills in data analysis!

Together, let's transform your data science aspirations into reality!

"Evan's course is a must for anyone diving into data science. NumPy, Pandas, data wrangling, and machine learning concepts were explained flawlessly. Great experience overall!"

What you’ll learn

In this course, you'll master essential techniques and concepts, including:

Introduction to Data Science

  • Understand the fundamentals of data science and its role in various industries.

  • Explore real-world applications of data science in sports analytics and beyond.

  • Get introduced to Python as a powerful tool for data analysis and manipulation.

Python Basics for Data Science

  • Learn introductory Python concepts and syntax.

  • Understand data types, structures, and variables in Python.

  • Explore conditional statements, loops, functions, and exception handling.

Exploring Data with NumPy & Pandas

  • Dive into NumPy for efficient array operations, linear algebra, and random number generation.

  • Learn how to use Pandas for data manipulation, cleaning, filtering, and summarization.

  • Explore data exploration techniques and basic data transformations.

Data Visualization & Modeling

  • Understand the importance of data visualization in data science.

  • Learn to create visualizations using the Matplotlib, Seaborn, and Plotly libraries.

  • Get introduced to basic modeling techniques like regression, clustering, and classification.

Case Studies & Machine Learning in Sports

  • Apply data wrangling techniques to real-world case studies.

  • Dive into sports analytics with data analysis, visualization, and modeling.

  • Explore machine learning algorithms like k-NN, k-means clustering, and hierarchical clustering in a sports context.

Join the FoundationZ of Data Science Course

Course Overview

Dive into our comprehensive course designed to lay the foundational knowledge required to excel in the world of data science. Explore fundamental concepts and techniques essential for mastering statistical modeling, data manipulation, and inference. Join us in this immersive journey and unlock the power of data science!

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Unleashing Foundational Concepts

Introduction to Data Science

  •  Understand the fundamental principles and applications of data science in various domains.

Python Essentials

  • Dive into introductory Python programming, syntax, variables, and data structures.

Conditional Statements and Loops

  • Learn about conditional statements, loops, and control flow in Python programming.

Functions and Libraries

  • Explore functions, libraries, and modules for efficient code organization and reuse.

Exception Handling

  • Understand error handling and exception handling techniques in Python.

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Data Manipulation & Analysis

NumPy Basics

  • Master NumPy arrays, array operations, and linear algebra for data manipulation and analysis.

Pandas DataFrames

  • Learn about Pandas DataFrames, data exploration, cleaning, filtering, and transformations.

Data Wrangling

  • Apply data wrangling techniques, including merging, slicing, and aggregating data for analysis.

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Data Visualization & Exploration

Introduction to Data Visualization

  • Explore the principles of data visualization and create compelling plots and charts.

Matplotlib and Seaborn

  • Dive into Matplotlib and Seaborn libraries for advanced data visualization and customization.

Interactive Visualizations

  • Learn to create interactive plots using tools like Plotly for enhanced data exploration.

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Introduction to Modeling Techniques

Clustering Algorithms

  • Explore clustering algorithms such as k-means and hierarchical clustering for data segmentation.

Regression and Classification

  • Understand regression and classification models, including k-NN

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Case Studies and Applications

EDA and Data Analysis

  • Perform exploratory data analysis, define problems, clean data, and derive insights.

Machine Learning Applications

  • Apply machine learning techniques to real-world problems in sports analytics and other domains.

meet Our Python Pro data science coach

Pat McFarlane

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Passionate about the intersection of data science and sports analytics.

As the Director of Predictive Modeling at the Philadelphia Phillies, I bring extensive experience in sports analytics and data science to our Python curriculum.

My background in aerospace engineering and passion for sports data will guide you in mastering Python for data analysis.

I hold a BS in Aerospace Engineering from the University of Notre Dame and a Master’s degree from MIT. This rigorous quantitative foundation has equipped me with the skills to develop predictive models for in-game strategy, player acquisition, and decision-making in baseball.

My career spans aviation safety, finance, consulting, and now sports analytics with the Phillies. This diverse experience allows me to blend my love for sports with data science expertise.

After jumpstarting your Python journey with Evan, get ready to join me in the "Python MachineZ in Sports" course to unlock take your machine learning skills to the next level. -- Coming soon (Fall 2024), will be sold separately

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Python MachineZ in Sports

After completing Foundationz of Data Science, get ready to learn with our Pro Data Science Coach, Pat McFarlane.

Here's a glimpse into what Pat will cover in his groundbreaking course, Python MachineZ in Sports. (Coming soon, Fall 2024 - sold separately):

Introduction to Advanced Machine Learning in

Sports Analytics

  • Dive deep into the world of machine learning in sports and understand how it's transforming the game.

Linear Regression and The Machine Learning Pipeline

  • Explore predictive modeling techniques and optimize machine learning pipelines for sports data by walking through an actual case study

Exploratory Data Analysis and Feature Engineering

  • Learn how to extract valuable insights from sports data through exploratory analysis and feature engineering.

Hyperparameter Tuning and Model Selection

  • Fine-tune your machine learning models and select the best algorithms for accurate predictions.

Model Performance Evaluation

  • Evaluate model performance using advanced metrics to ensure reliability and effectiveness.

Automating Machine Learning Pipelines

  • Streamline your data analysis workflows and automate repetitive tasks for efficiency.

Generalized Linear Models

  • Apply generalized linear models to analyze complex sports data and make data-driven decisions.

Generalized Additive Models

  • Utilize additive models to uncover hidden patterns and trends in sports analytics.

Tree-based Methods

  • Harness the power of decision trees and ensemble methods for accurate predictions in sports.

Model Interpretability

  • Understand model interpretability to explain predictions and gain actionable insights.

Introduction to Applied Bayesian Statistics

  • Learn Bayesian analysis techniques to enhance decision-making in sports analytics, prepare for PyMC.

What Industry Experts Are saying About Athlyticz

Discover what our students have to say about their experience with AthlyticZ:

"Here's your chance to learn future sports data gurus!"

"AthlyticZ has completely transformed the learning approach to data science through the use of sports-based problems. The course structure is intuitive, the content is comprehensive, the instructors are the best of the best, and the practical projects have immediate impact to students."

BILL GEIVETT M.ED.

PRESIDENT @ IMA TEAM

AUTHOR: DO YOU WANT TO WORK IN BASEBALL?

SR. VP: COLORADO ROCKIES 2001-2014

ASST. GM: LOS ANGELES DODGERS 1998-2000

"Empowering and Engaging"

"I've always been intrigued by the intersection of sports analytics and data science. AthlyticZ provides students with the perfect platform to explore this passion. The hands-on projects are particularly empowering, allowing them to apply theoretical concepts to real-world scenarios."

BRAD SMITH PHD

SENIOR PERFORMANCE ANALYST @ UNIVERSITY OF NEBRASKA

SPORTS ANALYTICS PROFESSOR, DATA SCIENCE PROGRAM @ NORTHWESTERN

PLAYER DEVELOPMENT ANALYST @ NEW YORK YANKEES 2018-2021

How We Conduct Our Course

At AthlyticZ, we've designed our course structure to empower your learning journey at your own pace, ensuring flexibility and accessibility.

Prerecorded Video Lessons

Delve into our comprehensive course content with prerecorded video lessons, allowing you to learn at your convenience and revisit concepts as needed.

Assignments and Exercises

Engage with assignments and exercises that reinforce your understanding of key concepts and help you build practical skills.

Continuous Assessment

Benefit from quizzes and assessments integrated throughout the course, providing you with ongoing feedback on your progress and understanding.

Hands-On Projects

Apply your knowledge to real-world projects, including both minor and major assignments, where you'll solve sports analytics problems using the skills you've acquired.

Supplementary Resources

Learn from additional resources, including readings and videos provided directly from the instructor, to complement the primary lessons and enhance the learning experience.

Interactive Features

Utilize interactive features within each lesson, including note-taking capabilities and custom-built IDEs with preloaded code, ensuring an immersive and engaging learning environment.

FoundationZ of Data Science

Course Information

  • 65+ Lessons of engaging content ~ 25 hours

  • Asynchronous, self-paced learning

  • Pre-recorded video lessons for flexible scheduling

  • Interactive Features: Quizzes throughout the course to reinforce learning

  • Supplementary Resources: Access to downloadable slides, readings, and additional materials

  • Hands-On Projects: Dive into major case study projects tailored to your interests

  • Virtual Machines: Immerse yourself in our customized IDE solutions for real world programming experience.

$599 usd

$349 usd

Frequently Asked Questions

1. Can I expense this course with my employer?

Discover the transformative power of mastering data science with our "Foundationz of Data Science" course.

Here's how your employer can leverage our course:

  • Streamline Data Analysis

  • Equip your team with essential Python skills to streamline data analysis processes, leading to faster insights and informed decision-making.

  • Optimize Workflows

  • Create customized data workflows tailored to your company's needs, optimizing efficiency and reducing manual data manipulation tasks.

  • Cost-Efficient SolutionsSave on commercial software expenses by utilizing open-source Python packages and tools for comprehensive data analysis and visualization.

    • Empower your team to excel in data analysis and drive business growth with our comprehensive "Foundationz of Data Science" course.

2. Do I need access to any commercial software?

No, you won't need any commercial software for this course.

3. Does the course assume extensive knowledge of Python?

No - this is an introductory course in Python to jumpstart your data science journey.

4. Is the course graded? What defines successful completion?

Evaluation is based on the completion of course work rather than "correct answers." Successful completion entails:

• 80% or higher on all quizzes

• 100% of modules completed

Upon meeting these criteria, you'll receive a certificate of completion.

5. What if I need to drop out? Is there a refund policy?

At AthlyticZ, we're committed to your success and satisfaction throughout your learning journey.Our refund policy is as follows:You can drop the course within 3 days of commencement for a full refund. After this date, refunds are not provided.

No refunds will be granted if you have completed 25% or more of the course material, regardless of the time elapsed since the course began.

Thank you for choosing AthlyticZ for your educational needs.

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