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