Game-Development Advanced Premium

Esports Game Analytics Virtual Internship

In this advanced Esports Game Analytics Virtual Internship, students will learn to leverage data science and machine learning techniques to optimize player performance, team strategies, and tournament outcomes. They will gain hands-on experience in analyzing game data, developing predictive models, and applying data-driven insights to enhance the competitive landscape of esports.

weeks
6 tasks
0 enrolled
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Track price: $49.00

Track Overview

This track provides hands-on experience and real-world projects to build your skills.

Tasks & Milestones

Esports Data Exploration

Advanced

In this task, students will explore and analyze a dataset of esports match data, identifying key metrics and patterns that can inform strategic decision-making.

10 hours

Player Performance Prediction

Advanced

In this task, students will develop a machine learning model to predict individual player performance based on historical data.

20 hours

Tournament Outcome Prediction

Advanced

In this task, students will develop a machine learning model to predict tournament outcomes based on team and player data.

20 hours

Winning Strategy Analysis

Advanced

In this task, students will analyze game data to identify winning strategies and team compositions, and develop recommendations to improve team performance.

20 hours

Esports Decision-Making Simulation

Advanced

In this task, students will apply their data analysis and communication skills in a simulated esports decision-making scenario.

15 hours

Esports Analytics Consulting Project

Advanced

In this capstone task, students will work with an esports organization to address a specific data-driven challenge.

40 hours

Prerequisites

  • • Proficiency in Python, SQL, and data analysis
  • • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch)
  • • Understanding of esports game mechanics and competitive landscape

Certificate

Certificate of Completion

Earn a certificate upon successful completion