Free Course Download100% Free Direct MP4 LinksUdemyAI, Machine Learning & Data Science2026-7 Edition

Download Simulation Modeling for Data Science with Python and AI Course for Free

Download the complete Simulation Modeling for Data Science with Python and AI video course for free with high-definition MP4 video lectures, project exercise archives, and step-by-step masterclasses. Learn offline at your own pace with zero paywalls or recurring subscriptions.

59Lectures

15.5Total Hours

2041.1MB Total Size

MP4 / 1080p HD

Instructor: Senior Industry Specialist

English

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Introduction Why We Need Simulation Modeling

MP4 HD18m•39.36 MB

Stream

Mini-Lab Solution Pick Distributions and Validate

MP4 HD1h•132.02 MB

Stream

Master template walkthrough, part 1

MP4 HD26m•56.51 MB

Stream

Master template walkthrough, part 2

MP4 HD24m•52.95 MB

Stream

Reading a worked example (MC loan portfolio)

MP4 HD34m•73.80 MB

Stream

Generating code from a spec — live demo

MP4 HD38m•82.83 MB

Stream

Validating AI-generated code (three layers)

MP4 HD49m•108.66 MB

Stream

Lab Solution - Running Generated Simulation

MP4 HD20m•44.37 MB

Stream

Why specs beat code

MP4 HD12m•25.84 MB

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The universal model anatomy

MP4 HD36m•79.95 MB

Stream

What is a distribution

MP4 HD27m•59.26 MB

Stream

Continuous distributions — Uniform, Normal, Lognormal

MP4 HD14m•30.45 MB

Stream

Outcome distributions — Bernoulli, Beta

MP4 HD16m•34.61 MB

Stream

Event-time distributions — Exponential, Poisson

MP4 HD12m•27.09 MB

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Expert-estimate distributions — Triangular

MP4 HD18m•39.69 MB

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Mini-lab - Pick Distributions and Validate

MP4 HD3m•6.49 MB

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What Monte Carlo is, and what it isn't

MP4 HD14m•29.87 MB

Stream

Lab - Monte Carlo Base Model

MP4 HD4m•9.46 MB

Stream

Lab Results - Monte Carlo Base Model

MP4 HD4m•8.72 MB

Stream

Interlude — How many replications are enough

MP4 HD5m•11.54 MB

Stream

Lab - Correlated Defaults

MP4 HD12m•26.09 MB

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Lab - Policy Levers

MP4 HD2m•3.52 MB

Stream

Lab - Stress Scenarios

MP4 HD3m•7.24 MB

Stream

Lab - Communicating Results

MP4 HD6m•12.66 MB

Stream

Monte Carlo Takeaways

MP4 HD2m•4.95 MB

Stream

What Discrete Event is, and what it isn't

MP4 HD16m•34.24 MB

Stream

a Introduction to Baseline M M c Queue Model

MP4 HD5m•11.65 MB

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b Lab 1 Base Clinic Model

MP4 HD1h 10m•153.30 MB

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Interlude — Warm-up periods and steady state

MP4 HD3m•5.78 MB

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a Introduction to Realistic Arrival and Service Times

MP4 HD5m•11.46 MB

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b Lab 2 Realistic Arrival and Service Times

MP4 HD29m•63.12 MB

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c Lab 2 Sidebar Fitting a Distribution and Calculating Sigma

MP4 HD15m•32.19 MB

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a Introduction to Resource Policy Levers

MP4 HD3m•6.72 MB

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b Lab 3 Resource Policy Levers

MP4 HD1h 5m•142.48 MB

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a Introduction to Stress Scenarios

MP4 HD4m•9.68 MB

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b Lab 4 Stress Scenarios

MP4 HD25m•54.10 MB

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a Introduction Communicating Results

MP4 HD11m•25.08 MB

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b Lab Communicating Results

MP4 HD22m•48.37 MB

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Discrete Event Simulation Takeaways

MP4 HD7m•15.69 MB

Stream

What System Dynamics is, and what it isn't

MP4 HD5m•10.83 MB

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Stocks, Flows, Feedback and Delays The Bullwhip Effect

MP4 HD21m•46.52 MB

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a Introduction to Production Capacity Demo

MP4 HD6m•12.85 MB

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b Production Capacity Demo

MP4 HD29m•64.30 MB

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Mini-Lab Turn the Dials

MP4 HD10m•21.14 MB

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b Mini-Lab Turn the Dials Solution

MP4 HD12m•25.60 MB

Stream

When to Use System Dynamics

MP4 HD9m•20.14 MB

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System Dynamics Takeaways

MP4 HD1m•3.05 MB

Stream

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What You'll Master in this Free Download Course

Use a spec-first AI workflow: write a structured model spec, generate working Python with Claude or ChatGPT, and iterate without coding from scratch

Answer real business questions under uncertainty, from capital reserves to staffing plans to product launches, with models you build yourself

Validate AI-generated code in three layers (read, assert, stress-test) so you can defend your results to a skeptical stakeholder

Run the what-if scenarios analytics and ML can’t: simulate futures with no historical precedent and report them with confidence intervals

Build a Monte Carlo loan portfolio risk model with correlated defaults, policy levers, and recession stress scenarios

Build a discrete-event clinic patient-flow model with realistic arrivals, peak-aware staffing, and an ops manager dashboard

Choose the right paradigm for a new problem (Monte Carlo, discrete-event, system dynamics, agent-based) and the right distribution for each uncertain input

Communicate simulation results in a one-page deliverable that earns the model the right to be acted on

and …

About this Free Download Course

Simulation Modeling for Data Science with Python and AI is a course on how to use simulation techniques, Python programming, and AI to model and analyze complex systems, published by Udemy Online Academy. Designed for data scientists, Python developers, engineers, researchers, and aspiring AI professionals, this course explores how simulation can be used to understand system behavior, test scenarios, estimate outcomes, and support data-driven decision making. Learners will work with probability, random variables, statistical distributions, Monte Carlo simulation, discrete event modeling, data analysis, and simulation workflows with the help of AI.In this valuable course, instead of learning patterns from the past, we model how the system itself works and then run thousands of possible scenarios to understand a wide range of possible outcomes. Simulation modeling complements the analytics, machine learning, and simulation you already know, allowing you to answer questions about new situations. If you can read Python and have ever provided analytics, you have the prerequisites. You won’t be writing code from scratch, but you will choose modeling parameters, validate the generated code using structured techniques, and communicate the results in a way that managers and executives can act on.

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Yes! If this course includes downloadable source code, exercise assets, or templates, they are available in the "Course Exercise Files & Project Archives" section as standard ZIP files for free download.

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