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Certified Esports Data Analyst (CEDA)

Duration: 3 Months (48 Hrs)

The National Institute of Robotics & Artificial Intelligence (NIRA) is a leading institution dedicated to fostering innovation and skills in eSports and data science. With a mission to bridge academic excellence and industry needs, NIRA offers cutting-edge programs to empower aspiring professionals with data-driven skills for the eSports industry.

Backed by expert faculty, advanced analytics labs, and partnerships with eSports organizations, NIRA’s curriculum emphasizes hands-on learning in performance analysis, fan engagement, and strategic decision-making. Our programs nurture innovation through incubators and support for aspiring data scientists and analysts.

Whether you aim to upskill, transition into eSports analytics, or lead data-driven strategies, NIRA is your gateway to shaping the future of competitive gaming.

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Registration Fees

₹ 1500

non-refundable

Course Fees

₹ 55000.00

Flexible EMI options available. No interest or hidden charges. Start learning now, pay later.

Batch Start

1 Aug, 2025

Duration

3 Months (48 Hrs)

Develop skills in streaming, video editing, and personal branding for platforms like Twitch and YouTube.

Eligibility: 10 + 2 (Preferred), Bachelor's degree (any discipline), basic math/statistics knowledge recommended.

Duration: 3 Months (48 Hrs)

Batch Start Date: 1 Aug, 2025

Batch Size: 10/Batch

Courses and Certification Conduct Policy:

Programme Summary

The eSports Analyst / Data Scientist Certification Program is a 3-month virtual course designed to equip participants with skills to analyze team and player performance, fan engagement, and game statistics. Tailored for data enthusiasts and gaming professionals, this program covers statistical modeling, predictive analytics, and data visualization. Participants will build a portfolio showcasing their ability to derive actionable insights for eSports teams and platforms.

Programme Highlights

The NIRA eSports Analyst / Data Scientist Certification Program is ideal for individuals from diverse backgrounds, including data science, statistics, or gaming. It blends analytical techniques with eSports-specific applications to drive performance and engagement.

Students will explore key areas such as:

  • Player and team performance analysis
  • Fan engagement and social media analytics
  • Predictive modeling for match outcomes
  • Data visualization and reporting

The hands-on curriculum ensures participants master tools and techniques to thrive in the dynamic eSports industry.

20+ Case Studies

24+ Office Hours Provided by the Programme Leader

  • Weekly live sessions with NIRA faculty for doubt-clearing and guidance.
  • Curated panel of industry experts as programme leaders.
  • Quizzes, assignments, and discussions finalized closer to the start.
  • Graded assignments with support from domain-expert programme leaders.

Tools Covered

Participants will gain proficiency in industry-standard tools for eSports analytics, including:

  • Python: For data analysis, machine learning, and scripting.
  • R: Statistical analysis and visualization.
  • SQL:Database management for game and fan data.
  • Tableau: Interactive dashboards for performance insights.
  • Pandas & NumPy: Data manipulation and analysis in Python.
  • Power BI: Business intelligence for fan engagement analytics.
  • Excel: Advanced spreadsheet analysis for quick insights.

These tools empower participants to analyze data and build impactful portfolios.

NIRA Certificate: Passport of Your Success

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Program Structure:

Module 1: Introduction to eSports Analytics
  • Overview of eSports ecosystems and data sources.
  • Key metrics:Player stats, team performance, fan engagement.
  • Role of analytics in strategy and decision-making.
  • Career paths in eSports data science.
  • Outcome:Understand the role of data in eSports and its applications.
Module 2: Data Collection and Management
  • Collecting game data (APIs, replay files, telemetry).
  • Database setup and querying with SQL.
  • Data cleaning and preprocessing with Python.
  • Ethical considerations in eSports data usage.
  • Outcome:Gather and prepare data for analysis.
Module 3:Statistical Analysis and Modeling
  • Descriptive statistics for performance metrics.
  • Predictive modeling with machine learning (regression, classification).
  • Time-series analysis for in-game trends.
  • A/B testing for fan engagement strategies.
  • Outcome: Apply statistical techniques to derive insights.
Module 4: Data Visualization and Reporting
  • Creating dashboards with Tableau and Power BI.
  • Visualizing player and team performance metrics.
  • Communicating insights to non-technical stakeholders.
  • Building automated reporting pipelines.
  • Outcome:Present data-driven insights effectively.
Module 5: Strategy Development and Collaboration
  • Translating data into actionable team strategies.
  • Working with coaches and players to implement insights.
  • Fan engagement optimization through analytics.
  • Portfolio project: End-to-end analytics for an eSports event.
  • Outcome: Deliver strategic value through data analysis.
Learning Outcome

Upon completion, participants will:

  • Master data analysis for player, team, and fan metrics.
  • Build predictive models to inform eSports strategies.
  • Create professional-grade visualizations and reports. .
  • Develop a portfolio showcasing analytics projects.
  • Be prepared for roles like eSports Analyst, Data Scientist, or Strategy Consultant.

Case Studies

Case Study 1

Analyzing player performance metrics for a CS2 tournament to optimize team strategy.

Case Study 2

Predicting match outcomes using historical data in Dota 2.

Case Study 3

Measuring fan engagement through social media metrics for a Valorant event.

Case Study 4

Creating a performance dashboard for a PUBG team to track KPIs.

Who Is This Programme For?

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