Using Python for Data Science and Supply Chain Analytics

Learn Python, Supply Chain Data Science, Linear Programming, Forecasting, Pricing and Inventory Management.

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Course curriculum

1. Segment - 01 - Introduction
2. Segment - 02 - Why we Need to Learn Coding
3. Segment - 03 - Curriculum
4. Segment - 04 - Plan of Attack
5. Segment - 05 - Supply Chain Visualization
6. Segment - 06 - Cost and Service Dynamics
7. Segment - 07 - Service Level and Product Characteristics
8. Segment - 08 - Customer and Supplier Characteristics
9. Segment - 09 - Supply Chain Views
10. Segment - 10 - The Financial Flow
11. Segment - 11 - Why is Supply Chain Complicated
1. Segment - 12 - Introduction
2. Segment - 13 - Types Of Data in Supply Chain
3. Segment - 14 - Data From Suppliers
4. Segment - 15 - Data From Production
5. Segment - 16 - Data From Stocks
6. Segment - 17 - Data From Sales and Customers
7. Segment - 18 - Why we Need to Learn Data Science
8. Segment - 19 - Analytics Types
1. Segment - 20 - Python
2. Segment - 21 - Downloading Anaconda
3. Segment - 22 - Installing Anaconda
4. Segment - 23 - Spyder Overview
5. Segment - 24 - Jupiter Notebook Overview
6. Segment - 25 - Python Libraries
7. Segment - 26 - Inventory Package
1. Segment - 27 - Introduction
2. Segment - 28 - Dataframes
3. Segment - 29 - Arithmetic Calculations with Python
4. Segment - 30 - Lists
5. Segment - 31 - Dictionaries
6. Segment - 32 - Arrays
7. Segment - 33 - Importing Data in Python
8. Segment - 34 - Subsetting Data Frames
9. Segment - 35 - Conditions
10. Segment - 36 - Writing functions
11. Segment - 37 - Mapping
12. Segment - 38 - For Loops
13. Segment - 39 - For Looping a Function
14. Segment - 40 - Mapping on a Data Frame
15. Segment - 41 - For Looping on a Data Frame
16. Segment - 42 - Summary
17. Segment - 43 - Assignment
18. Segment - 44 - Assignment Answer 1
19. Segment - 45 - Assignment Answer 2
1. Segment - 46 - Introduction
2. Segment - 47 - Measures of Centrality and Spread
3. Segment - 48 - Calculating the Mean
4. Segment - 49 - Calculating the Median
5. Segment - 50 - Measures of Spread
6. Segment - 51 - Percentiles
7. Segment - 52 - Correlations: Subsetting Cars Dataset
8. Segment - 53 - Correlations of Continuous Variables
9. Segment - 54 - Correlation Plots
10. Segment - 55 - Correlation Thresholds
11. Segment - 56 - Detecting Outliers
12. Segment - 57 - Outliers in Python
13. Segment - 58 - Linear Regression
14. Segment - 59 - Introduction to Linear Regression
15. Segment - 60 - Linear Regression in Python
16. Segment - 61 - Fitting the Linear Model
17. Segment - 62 - Importance of Distributions in Supply Chain
18. Segment - 63 - Chi- Square Tests
19. Segment - 64 - Distributions in Excel
20. Segment - 65 - Distributions Chi-Square Tests
21. Segment - 66 - Cover for 90% of Demand
22. Segment - 67 - Assignment
23. Segment - 68 - Assignment Answer
24. Segment - 69 - Distributions in Python
25. Segment - 70 - Testing for Several Distributions
26. Segment - 71 - Summary
27. Segment - 72 - Assignment
28. Segment - 73 - Assignment Answer
1. Segment - 74 - Manipulation Introduction
2. Segment - 75 - Dropping Duplicates and NAs
3. Segment - 77 - Conversions
4. Segment - 76 - Conversions Lecture
5. Segment - 78 - Filtration
6. Segment - 79 - Imputations
7. Segment - 80 - Indexing Tutorial
8. Segment - 81 - Slicing Index
9. Segment - 82 - Manipulation Lecture
10. Segment - 83 - Groupby
11. Segment - 84 - Slicing the Groupby
12. Segment - 85 - Dropping Levels
13. Segment - 86 - The Proper Form
14. Segment - 87 - Pivot Tables
15. Segment - 88 - Aggregate Function in Pivot Table
16. Segment - 89 - Melting the Data
17. Segment - 90 - Left Join
18. Segment - 91 - Inner and Outer Join
19. Segment - 92 - Joining in Python
20. Segment - 93 - Inner, Left Join and Full Join (outer)
21. Segment - 94 - Summary
22. Segment - 95 - Assignment
23. Segment - 96 - Assignment Answer 1
24. Segment - 97 - Assignment Answer 2
25. Segment - 98 - Assignment Answer 3
26. Segment - 99 - Assignment Answer 4
27. Segment - 100 - Assignment Answer 5
1. Segment - 101 - Date Introduction
2. Segment - 102 - Datetime
3. Segment - 103 - Last Purchase Date and Recency
4. Segment - 104 - Recency Histogram
5. Segment - 105 - Modeling Inter-Arrival Time
6. Segment - 106 - Modeling Inter Arrival Time 2
7. Segment - 107 - Modeling Inter Arrival Time 3
8. Segment - 108 - Resampling
9. Segment - 109 - Rolling Time Series
10. Segment - 110 - Rolling Time Series 2
11. Segment - 111 - Summary
12. Segment - 112 - Assignment
13. Segment - 113 - Assignment Answer
1. Segment - 114 - Introduction
2. Segment - 115 - Line Plot Part 1
3. Segment - 116 - Line Plot Part 2
4. Segment - 117 - Scatter Plot
5. Segment - 118 - Count Plot
6. Segment - 119 - Bar Plot
7. Segment - 120 - Distribution Plots
8. Segment - 121 - Box Plots
9. Segment - 122 - Histograms
10. Segment - 123 - Pair Plots
11. Segment - 124 - Visualization Summary
12. Segment - 125 - Assignment
13. Segment - 126 - Assignment Answer 2
1. Segment - 127 - Introduction
2. Segment - 128 - Segmentation
3. Segment - 129 - Importance of ABC Analysis
4. Segment - 130 - Multi Criteria Segmentation
5. Segment - 131 - Transforming the Data for Excel
6. Segment - 132 - ABC Analysis in Excel
7. Segment - 133 - Assignment
8. Segment - 134 - ABC in Python
9. Segment - 135 - Multi-Criteria ABC Analysis
10. Segment - 136 - Multi-Criteria ABC in Python
11. Segment - 137 - Supplier Segmentation 1
12. Segment - 138 - Supplier Segmentation 2
13. Segment - 139 - Supplier Segmentation In Python
14. Segment - 140 - Value Index
15. Segment - 141 - Visualizing Krajic
16. Segment - 142 - Summary
17. Segment - 143 - Assignment ABC
18. Segment - 144 - Assignment answer
1. Segment - 145 - Why We Need Forecasts
2. Segment - 146 - Qualitative and Quantitative Forecasting
3. Segment - 147 - Optimistic and Pessimistic Forecasting
4. Segment - 148 - Time Components
5. Segment - 149 - Preparing the Data for Regression
6. Segment - 150 - Multi Linear Regression in Excel Part 1
7. Segment - 152 - Assignment
8. Segment - 153 - Regression in Python Part 1
9. Segment - 154 - Regression in python Part 2
10. Segment - 155 - Initializing a Date Range for Forecasting
11. Segment - 156 - Forecasting
12. Segment - 157 - Forecasting Summary
13. Segment - 158 - Assignment Questions
14. Segment - 151 - Multi Linear Regression in Excel Part 2
15. Segment - 159 - Assignment 1
16. Segment - 160 - Assignment 2
1. Segment - 161 - Time Series Introduction
2. Segment - 162 - Accuracy Measures
3. Segment - 163 - Preparing the Data for Time-series
4. Segment - 164 - Getting the Time Series Components: Lecture
5. Segment - 165 - Getting the Time Series Components
6. Segment - 166 - Components Uses
7. Segment - 167 - Arima Models
8. Segment - 168 - Stationarity Test in Python
9. Segment - 169 - Arima in Python
10. Segment - 170 - Arima Diagnostics
11. Segment - 171 - Grid Search
12. Segment - 172 - For Looping ARIMA
13. Segment - 173 - Error Handling
14. Segment - 174 - Fitting the Best Model
15. Segment - 175 - Mean Absolute Error
16. Segment - 176 - Arima Comparison
17. Segment - 177 - Exponential Smoothing
18. Segment - 178 - Exponential Smoothing in Python
19. Segment - 179 - Comparing Exponential Smoothing Models
20. Segment - 180 - Time Series Summary
21. Segment - 181 - Assignment
22. Segment - 182 - Assignment Explanation 1
23. Segment - 183 - Assignment Explanation 2
24. Segment - 184 - Assignment Explanation 3
25. Segment - 185 - Assignment Explanation 4
1. Segment - 186 - Product Classifications
2. Segment - 187 - Demand Classification
3. Segment - 188 - Holidays
4. Segment - 189 - Coefficient of Variation Squared
5. Segment - 190 - Preparing for Average Demand Interval
6. Segment - 191 - Average Demand Interval
7. Segment - 192 - Durations
8. Segment - 193 - Coerce Duration
9. Segment - 195 - Conclusion
10. Segment - 196 - Summary
11. Segment - 197 - Assignment
12. Segment - 194 - Classifications
13. Segment - 198 - Assignment Explanation
1. Segment - 199 - Introduction
2. Segment - 200 - Waiting Lines
3. Segment - 201 - Simulation Example Demo
4. Segment - 202 - Simulation Excel
5. Segment - 203 - Simulation Assignment
6. Segment - 204 - Simulating Waiting Time in Python
7. Segment - 205 - 1000 Simulations
8. Segment - 206 - Downloading R
9. Segment - 207 - Installing R
10. Segment - 208 - Installing Rpy2
11. Segment - 209 - Simulation with Queue Computer
12. Segment - 210 - Multiple Resources
13. Segment - 211 - Getting the Optimum Number of Servers
14. Segment - 212 - Capacity Constrains
15. Segment - 213 - Multiple Service Lecture
16. Segment - 214 - Multiple Service with Queue Computer
17. Segment - 216 - Summary
18. Segment - 217 - Assignment
19. Segment - 215 - Mean Waiting Time of the System
20. Segment - 218 - Assignment Explanation
1. Segment - 219 - Optimization Introduction
2. Segment - 220 - Problem Formulation
3. Segment - 221 - Model in Excel
4. Segment - 222 - Installing Pulp
5. Segment - 223 - Model In Python
6. Segment - 224 - Assignment
7. Segment - 225 - Assignment Explanation
8. Segment - 226 - Transport Problem in Excel
9. Segment - 227 - Transport Problem in in Pulp Part 1
10. Segment - 228 - Transport Optimization Part 2
11. Segment - 229 - Formulating Supply Constraint
12. Segment - 230 - Solving the Model
13. Segment - 231 - Assignment
14. Segment - 232 - Assignment Answer
15. Segment - 233 - Production Planning
16. Segment - 234 - Production Scheduling
17. Segment - 235 - Production Scheduling in Python
18. Segment - 236 - Constraints Definition
19. Segment - 237 - Model Sensitivity
20. Segment - 238 - Summary
21. Segment - 239 - Production Scheduling Assignment
22. Segment - 240 - Assignment Explanation
1. Segment - 241 - Introduction
2. Segment - 242 - Why We Need Inventory?
3. Segment - 243 - Inventory Strategies
4. Segment - 244 - Inventory Types and EOQ
5. Segment - 245 - Total Logistics Cost and Total Relevant Cost
6. Segment - 246 - Economic Order Quantity with Excel
7. Segment - 247 - EOQ with Discounts
8. Segment - 248 - EOQ Sensitivity
9. Segment - 249 - EOQ in Python
10. Segment - 250 - EOQ Practical
11. Segment - 251 - EOQ with Lead-Time
12. Segment - 252 - EOQ with Lead-Time in Python
13. Segment - 253 - Summary Part 1
14. Segment - 254 - Summary Part 2
15. Segment - 255 - Assignment
16. Segment - 256 - Assignment Answer 1
17. Segment - 257 - Assignment Answer 2
1. Segment - 258 - Introduction
2. Segment - 259 - Variability In Supply Chain
3. Segment - 260 - Demand Lead-Time and Sigma Demand Lead-Time
4. Segment - 261 - Calculating Average Daily Demand
5. Segment - 262 - Method 1 for Safety Stock Calculation
6. Segment - 263 - Method 2 for Safety Stock Calculation
7. Segment - 264 - Preparing the Data for Safety Stock Calculations
8. Segment - 265 - Calculating Average Demand
9. Segment - 266 - Segmentation of Data for Service Level
10. Segment - 267 - Reorder Point for All Skus
11. Segment - 268 - Reorder Point Conclusion
12. Segment - 269 - Lead-Time variability
13. Segment - 270 - Lead-Time Variability in Python
14. Segment - 271 - Summary
15. Segment - 272 - Assignment
16. Segment - 273 - Assignment Explanation
1. Segment - 274 - Inventory Policies-1
2. Segment - 275 - Inventory Policies-2
3. Segment - 276 - Min Q Demonstration
4. Segment - 277 - Min Q Lecture
5. Segment - 278 - Min Q in Excel
6. Segment - 279 - Periodic Review Demonstration
7. Segment - 280 - Periodic Review Lecture
8. Segment - 281 - Periodic Review Demonstration in Excel
9. Segment - 282 - Min Max Demonstration
10. Segment - 283 - Min Max Policy
11. Segment - 284 - Min Max Example in Excel
12. Segment - 285 - Base Stock Demonstration
13. Segment - 286 - Base Stock Policy
14. Segment - 287 - Base Stock Policy in Excel
15. Segment - 288 - Assignment
16. Segment - 289 - S,Q Policy in Python
17. Segment - 290 - Min Max Policy
18. Segment - 291 - Min Max Simulation
19. Segment - 292 - Periodic Policy in Python
20. Segment - 293 - Hybrid Policy
21. Segment - 294 - Base Stock Policy
22. Segment - 295 - Comparing All Policies
23. Segment - 296 - Summary
24. Segment - 297 - Inventory Simulations Assignment-1
25. Segment - 298 - Inventory Simulation Assignment-2
1. Segment - 299 - Introduction
2. Segment - 300 - Seasonal Products
3. Segment - 301 - Point of Maximum Profit
4. Segment - 302 - How Much I will Sell?
5. Segment - 303 - Data Table
6. Segment - 304 - Critical Ratio
7. Segment - 305 - Critical Ratio in Excel
8. Segment - 306 - What's Actually Happening?
9. Segment - 307 - Critical Ratio in Python
10. Segment - 308 - Preparing the Data for MPN
11. Segment - 309 - Creating a Margin of Error
12. Segment - 310 - Applying MPN on All Data
13. Segment - 311 - Conclusion
14. Segment - 312 - Seasonal Inventory Summary
15. Segment - 313 - Assignment Solution
16. Segment - 314 - Seasonal Inventory Answer
1. Segment - 315 - Introduction.
2. Segment - 316 - Pricing History
3. Segment - 317 - Why Pricing is Important?
4. Segment - 318 - Customers Perception of Price
5. Segment - 319 - Pricing Mechanisms
6. Segment - 320 - Commodities
7. Segment - 321 - Price Response Function
8. Segment - 322 - Price Response Function in Python
9. Segment - 323 - Simulating the Demand
10. Segment - 324 - Point of Maximum Profit
11. Segment - 325 - Assignment
12. Segment - 326 - Assignment Explanation
13. Segment - 327 - Elasticity Introduction
14. Segment - 328 - Elasticity
15. Segment - 329 - Linear Elasticity with Inventory
16. Segment - 330 - Parsing Dates
17. Segment - 331 - Getting List of Unique Skus
18. Segment - 332 - Linear Elasticity
19. Segment - 333 - Error Handling for Linear Elasticity
20. Segment - 334 - Conclusion
21. Segment - 335 - Single Optimization Summary
22. Segment - 336 - Assignment
23. Segment - 337 - Explanation
1. Segment - 338 - Introduction
2. Segment - 339 - Logistic Regression
3. Segment - 340 - Logistic Modeling with Inventory
4. Segment - 341 - Comparison between Logistic and Linear
5. Segment - 342 - Logit For Looping
6. Segment - 343 - Logit Assignment
7. Segment - 344 - Logit Assignment Answer
1. Segment - 345 - Introduction
2. Segment - 346 - Competing Products
3. Segment - 347 - Relation Among Products
4. Segment - 348 - Multi-Variate Regression in Python
5. Segment - 349 - Multinomial Choice Models
6. Segment - 350 - Multinomial Logit Models
7. Segment - 351 - Multi Competing Products in Python
8. Segment - 352 - Summary
1. Segment - 353 - Introduction
2. Segment - 354 - Markdowns
3. Segment - 355 - Why we do Markdowns
4. Segment - 356 - Customers Segment to Markdowns
5. Segment - 357 - Problem Formulation
6. Segment - 358 - Markdowns for Multiple Periods
7. Segment - 359 - Setting up Solver
8. Segment - 360 - Salvage Value
9. Segment - 361 - Markdowns with Forecasting.
10. Segment - 362 - Sensitivity Analysis.
11. Segment - 363 - Markdowns for One Period
12. Segment - 364 - Assignment
1. Segment - 365 - RFM Analysis
2. Segment - 366 - Customer Segmentation Based on RFM.
3. Segment - 367 - Customer Recency in Python
4. Segment - 368 - Frequency and Monetary Value
5. Segment - 369 - Ranking
6. Segment - 370 - Grouping
7. Segment - 371 - Creating the Categories
8. Segment - 372 - Conclusion
1. Segment - 373 - Introduction to Machine Learning
2. Segment - 374 - Decision Tree Demo
3. Segment - 375 - Overfitting
4. Segment - 376 - Kmeans in Python
5. Segment - 377 - Centroids Visualization
6. Segment - 378 - Elbow Spree
7. Segment - 379 - Preparing the Data for Regression
8. Segment - 380 - Getting the Time Components
9. Segment - 381 - Encoding
10. Segment - 382 - Training the Models
11. Segment - 383 - KNN
12. Segment - 384 - KNN Grid Search
13. Segment - 385 - Lasso Grid Search
14. Segment - 386 - Regularization Importance in Lasso
15. Segment - 387 - Regularization Visualization
16. Segment - 388 - Case Study
17. Segment - 389 - Exploring the Banking Data
18. Segment - 390 - Preparing the Data
19. Segment - 391 - Logistic Regression without Grid Search
20. Segment - 392 - Pre Processing of Data
21. Segment - 393 - Grid Search
22. Segment - 394 - Confusion Matrix
23. Segment - 395 - AUC
24. Segment - 396 - Area Under Curve
25. Segment - 397 - Preparing for Pipelines
26. Segment - 398 - Pipelines for Four Models
27. Segment - 399 - Grid For Logistic Regression
28. Segment - 400 - Grids
29. Segment - 401 - For Looping Pipelines
30. Segment - 402 - Verbose
31. Segment - 403 - Pipeline Conclusion
32. Segment - 404 - Random Forest and Decision Tree Comparison
33. Segment - 405 - Randomized Search

About this course

Free
405 lessons
37 hours of video content

Using Python for Data Science and Supply Chain Analytics

Course curriculum

Module 1: Course Introduction

Module 2: Supply Chain Data

Module 3: Welcome to World of Python

Module 4: Python Programming Fundamentals

Module 5: Supply Chain Statistical Analysis

Module 6: Manipulation and Data Cleaning

Module 7: Working with Dates with Python

Module 8: Visualization with Matplotlib and Seaborn

Module 9: Segmentation

Module 10: Forecasting Basics

Module 11: Time Series Modeling

Module 12: Forecasting Segmentation

Module 13: Supply Chain Simulations

Module 14: Linear Programming in Python

Module 15: Inventory

Module 16: Inventory with Uncertainty

Module 17: Inventory Simulations

Module 18: Seasonal Inventory

Module 19: Consumer Behavior and Pricing

Module 20: Logit Price Response Function

Module 21: Multi Product Optimization

Module 22: Markdowns

Module 23: RFM Analysis

Module 24: Machine Learning

About this course