RA: Retail Management, Analytics with Excel & Python.
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“This is one of the three courses in the Retail Series by RA, each course can be taken independently.”
Master Retail management and analytics with Excel and Python
Retailers face fierce competition every day and keeping up with the new trends and customer preferences is a guarantee for excellence in the modern retail environment. one Keyway to excel in retail management is utilizing the data that is produced every day. It is estimated that We produce an overwhelming amount of data every day, roughly 2.5 quintillion bytes. According to an IBM study, 90% of the world’s data has been created in the last two years.
Retail analytics is the field of studying the produced retail data and making insightful data-driven decisions from it. as this is a wide field, I have split the Program into three parts.
Retail Management, Analytics with Excel & Python.
1- Understanding the retail environment.
2- Retail Formats.
3- Retail Fundamentals
2- Manipulation of Data with Pandas.
2-Working with Python for analytics.
3- Developing Forecasts with Excel.
4- Adjusting Product Prices to maximize revenue.
5- Forecasting In python with Deep learning and regression techniques, ANN and RNN.
6- Product placement strategies inside the stores.
Don’t worry If you don’t know how to code, we learn step by step by applying retail analysis!
*NOTE: Full Program includes downloadable resources and Python project files, homework and Program quizzes, lifetime access, and a 30-day money-back guarantee.
Who this Program is for:
· If you are an absolute beginner at coding, then take this Program.
· If you work in Retail and want to make data-driven decisions, this Program will equip you with what you need.
· If you are switching from Excel to a data science language. then this Program will fast-track your goal.
· If you are tired of doing the same analysis again and again on spreadsheets and want to find ways to automate it, this Program is for you.
Program Design
the Program is designed as experiential learning Modules, the first couple of modules are for retail fundamentals followed by Python programming fundamentals, this is to level all of the takers of this Program to the same pace. and the third part is retail applications using Data science which is using the knowledge of the first two modules to apply. while the Program delivery method will be a mix of me explaining the concepts on a whiteboard, Presentations, and Python-coding sessions where you do the coding with me step by step. there will be assessments in most of the sections to strengthen your newly acquired skills. all the practice and assessments are real retail use cases.
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1Curriculum summaryVideo lesson
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2Curriculum LayoutVideo lesson
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3What are retailers?Video lesson
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4IntroductionVideo lesson
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5Types of retailVideo lesson
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6Taking part of the value chainVideo lesson
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7VerticalsVideo lesson
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8Food and near food retailersVideo lesson
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9Comparison between food and near food retailersVideo lesson
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10General Merchandize retailersVideo lesson
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11Amazon Vs Barnes and nobleVideo lesson
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12Will online replace physical retail ?Video lesson
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13Multi-channel enviromentVideo lesson
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14Verticals typesVideo lesson
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15Quiz on Section 1Quiz
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28Importance of PricingVideo lesson
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29IntroVideo lesson
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30Linear RegrressionVideo lesson
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31Price Response functionVideo lesson
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32Logistic RegressionVideo lesson
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33Logistic Price Response functionVideo lesson
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34Linear Price Function EstimationVideo lesson
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35CorrectionVideo lesson
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36Logit Price functionVideo lesson
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37Simulating the price.Video lesson
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38Elasticity introVideo lesson
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39ELASTICITYVideo lesson
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40Elasticity fo logit and linearVideo lesson
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41AssignmentVideo lesson
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42AnswerVideo lesson
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43Response function variants- PolynomialVideo lesson
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44Some examples of elasticityVideo lesson
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45Willingness to payVideo lesson
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46Point of Maximum profitVideo lesson
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47SummaryVideo lesson
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48IntroVideo lesson
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49MarkdownsVideo lesson
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50Why we do Markdowns?Video lesson
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51Customer segments to markdownsVideo lesson
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52Problem formulations.Video lesson
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53Markdown for multiple periodsVideo lesson
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54setting up solverVideo lesson
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55Salvage valueVideo lesson
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56Markdowns with forecastingVideo lesson
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57Sensitivity analysisVideo lesson
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58Markdowns for one periodVideo lesson
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59AssignmentVideo lesson
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67IntroVideo lesson
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68DataframesVideo lesson
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69Arithmetic calculations with pythonVideo lesson
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70ListsVideo lesson
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71DictionariesVideo lesson
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72ArraysVideo lesson
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73Importing data in pythonVideo lesson
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74Subsetting dataframesVideo lesson
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75ConditionsVideo lesson
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76Writing functionsVideo lesson
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77MappingVideo lesson
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78for loopsVideo lesson
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79for looping a functionVideo lesson
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80Mapping on a dataframeVideo lesson
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81for looping on a dataframeVideo lesson
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82SummaryVideo lesson
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83AssignmentVideo lesson
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84Assignment answer1Video lesson
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85Assignment answer2Video lesson
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