Operations Research Analyst

Learning path

Take these courses in order, from beginner to mid-level.

1. 1

   Step 1: STEM Foundations: The Universal Skill Stack

   The shared base every STEM career uses: working with numbers and units, testing ideas fairly, handling data and code, and explaining your work.

   Level: Beginner4 modules · 12 lessons · 7h 18mAlso used in 34 other careers
2. 2

   Step 2: Foundations for Math, Statistics & Analytics Careers

   How statisticians, actuaries and operations research analysts work: the math they use, pairing it with code, credentials, evidence, and explaining results honestly.

   Level: Beginner3 modules · 9 lessons · 3h 44mAlso used in 2 other careers
3. 3

   Step 3: Digital Literacy for Tech & STEM Work

   The everyday computer, internet, safety and AI skills every tech and STEM job assumes you already have.

   Level: Beginner4 modules · 12 lessons · 6h 8mAlso used in 34 other careers
4. 4

   Step 4: Professional Communication & Teamwork

   Write clear emails and documents, present and run meetings, work well on teams, and navigate résumés, interviews and networking.

   Level: Beginner4 modules · 12 lessons · 7h 24mAlso used in 34 other careers
5. 5

   Step 5: Math for Tech & STEM

   The practical math behind tech and STEM work: numbers, algebra, functions, geometry, logic and counting, with short code exercises.

   Level: Beginner5 modules · 15 lessons · 7h 32mAlso used in 34 other careers
6. 6

   Step 6: Spreadsheets for Data Work

   Clean tables, correct formulas, lookups, pivot tables and honest charts in Google Sheets, LibreOffice Calc or Excel.

   Level: Beginner3 modules · 9 lessons · 6h 35mAlso used in 16 other careers
7. 7

   Step 7: Python Fundamentals

   Learn to program in Python from zero: values, decisions, loops, functions, data structures, files, modules and a small data project.

   Level: Beginner5 modules · 15 lessons · 9h 53mAlso used in 22 other careers
8. 8

   Step 8: Statistics Fundamentals

   Describe data, reason with probability, and draw honest conclusions from samples, with short fill-in-the-blank Python exercises.

   Level: Beginner4 modules · 12 lessons · 6h 50mAlso used in 14 other careers
9. 9

   Step 9: Intro to Data Analysis with Python

   Load, clean, reshape and explore real data with Python and pandas, then turn the results into clear findings.

   Level: Intermediate4 modules · 13 lessons · 12h 55mAlso used in 10 other careers
10. 10

    Step 10: Data Visualization & Storytelling

    Turn analysis into charts people read correctly: visual principles, matplotlib and seaborn, small multiples, dashboards and a short data story.

    Level: Intermediate3 modules · 9 lessons · 7h 29mAlso used in 3 other careers
11. 11

    Step 11: Calculus & Linear Algebra for STEM

    The calculus and linear algebra behind science, engineering and machine learning: derivatives, integrals, vectors, matrices, gradients and eigenvalues, with Python exercises.

    Level: Intermediate4 modules · 12 lessons · 7h 48mAlso used in 11 other careers
12. 12

    Step 12: Probability & Statistical Inference

    Model uncertainty with random variables and distributions, then estimate, test and update beliefs from data, with Python simulations you run in the browser.

    Level: Intermediate4 modules · 12 lessons · 9h 26mAlso used in 7 other careers
13. 13

    Step 13: Regression & Experimental Design

    Fit and check multiple regression and GLMs, design randomised, blocked and factorial experiments, and turn analyses into clear, reproducible reports for the researchers you work with.

    Level: Mid-level4 modules · 12 lessons · 8hAlso used in 5 other careers
14. 14

    Step 14: Optimization & Operations Research

    Model real decisions with linear and integer programming, networks, queues, simulation and decision trees, then present the results so managers act on them.

    Level: Mid-level4 modules · 12 lessons · 7h 32m

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