Stock Control and Inventory Dynamics with Excel & Python.

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Haytham Omar-Ph.D

14:52:18

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1 - Introduction

1 - Introduction.mp4

05:06

2 - Types of inventory.mp4

06:21

3 - Cycle inventory.mp4

07:02

4 - Holding cost and ordering cost.mp4

09:36

5 - Zara and seven eleven.mp4

04:55

6 - EOQ.mp4

03:54

7 - EOQOne product.mp4

12:59

7 - EOQ-Variaattions.xlsx

8 - EOQsame truck.mp4

12:37

9 - EOQmany suppliers.mp4

08:16

10 - Algorithm for flexible order subsetting.mp4

07:27

11 - Algorithm for flexible order subsettingpart2.mp4

06:24

12 - Product subset part3.mp4

07:41

13 - Algorithm for product subsetting step 4.mp4

10:18

13 - EOQ-Variaattions-solved.xlsx

14 - EOQ-DISCOUNTS-UNSOVED.xlsx

14 - Volume discounts.mp4

12:16

15 - Volume Discounts in Excel.mp4

08:59

16 - EOQ-DISCOUNTS-SOLVED.xlsx

16 - marginal discounts.mp4

14:06

17 - EOQ with limited time discounts.mp4

05:32

18 - Limited time discounts.mp4

05:19

19 - Demand Curve change with EOQ.mp4

11:48

20 - Summary.mp4

02:40

21 - Game plan.mp4

00:57

2 - Inventory aggregation metrics and distribution

22 - Introduction.mp4

06:26

23 - A brief on inventory policies.mp4

07:10

24 - Fill rate and service level for uncertain demand.mp4

04:37

25 - Bike Co.mp4

03:11

26 - Bike Co flow time and average inventory.mp4

07:48

27 - Bike Co Desired service level.mp4

06:19

28 - Bike co cycle service level.mp4

03:27

29 - Desired fill rate.mp4

12:43

30 - Inventory aggregation.mp4

06:07

31 - Shopico Example.mp4

02:19

32 - Scenario 1 Disaggregation.mp4

08:28

33 - Scenario 2 Aggregation.mp4

13:20

34 - HighMed.mp4

07:43

35 - HighMed Part 1.mp4

17:07

36 - HighMed Part 2.mp4

07:34

37 - Inventory Cost.mp4

06:44

38 - Which option is better.mp4

14:10

39 - Temporal aggregation.mp4

15:45

40 - Conclusion.mp4

06:13

41 - Summary.mp4

01:55

3 - Welcome to Python

42 - Python.mp4

01:35

43 - downloading Anaconda.mp4

01:34

44 - Installing Anaconda.mp4

01:03

45 - Spyder overview.mp4

11:38

46 - Jupiter Notebook overview.mp4

02:53

47 - Python Libraries.mp4

05:30

48 - inventorize.mp4

01:05

49 - Summary.mp4

01:08

4 - Python Programming Fundmentals

50 - Intro.mp4

07:24

50 - Python-Data-structures-cheat-sheet.pdf

51 - Dataframes.mp4

02:33

51 - Section-4.ipynb.zip

52 - Arithmetic calculations with python.mp4

08:30

52 - online-retail2.csv.zip

53 - Lists.mp4

06:34

54 - Dictionaries.mp4

05:01

54 - Pandas-Basics.pdf

55 - Arrays.mp4

03:14

56 - Importing data in Python.mp4

07:57

57 - Subsetting Dataframes.mp4

08:40

58 - Conditions.mp4

04:28

59 - Writing functions.mp4

08:00

60 - Mapping.mp4

02:14

61 - For loops.mp4

02:16

62 - For looping a function.mp4

04:14

63 - Mapping on a DataFrame.mp4

05:41

64 - For looping on a Dataframe.mp4

08:17

64 - python-cheat-sheet-intermediate.pdf

65 - Summary.mp4

08:33

66 - Assignment.mp4

02:10

66 - assignment-questions-python-fundmentals.docx

66 - cars.csv

66 - python-fundmentals-assignment.zip

67 - Assignment answer 1.mp4

05:44

68 - Assignment answer 2.mp4

09:58

5 - Inventory with Python

69 - Program for EOQ aalgorithm.mp4

02:14

70 - Revisiting BikeCo.mp4

07:49

70 - bikeco-unsolved.zip

71 - Cycle service level in python.mp4

07:12

72 - Expected item fill rate in python.mp4

06:13

73 - Goal seek function.mp4

10:46

74 - Desired fill rate.mp4

08:37

74 - bikeco.zip

75 - Revisiting EOQ with many suppliers.mp4

02:54

75 - eoq-not-solved.zip

76 - Introducing the case in python.mp4

04:17

77 - EOQ with inventorize.mp4

13:23

78 - Step 2 and step 3.mp4

09:22

79 - global order frequency for product subsetting.mp4

07:33

80 - Total cost of the system.mp4

10:58

80 - eoq-solved.zip

6 - Segmentation classification and inventory simulations

81 - Inventory Dynamics intro.mp4

03:30

82 - Why we need segmentation.mp4

09:42

83 - An example in Excel.mp4

01:39

84 - Product classfication.mp4

05:04

85 - ABC dynamic with inventorize.mp4

02:49

85 - sample.csv

85 - segmentation-inventory-not-solved.zip

86 - The long tail.mp4

10:25

87 - Category mix on multiple products.mp4

11:50

88 - Min max policy.mp4

15:58

89 - Min Q and Periodic Policy.mp4

12:47

90 - RsS and basestockpolicy.mp4

10:15

91 - Connecting demand with service level.mp4

11:14

92 - Running the simulation on all articles.mp4

17:39

93 - Understanding the results.mp4

09:25

93 - segmentation-inventory-solved.zip

94 - Assignment.mp4

04:21

94 - assignment-peridodic.zip

94 - assignment-review.xlsx

95 - Assignment solution.mp4

04:45

95 - assignment-peridodic.zip

96 - Summary.mp4

04:18

7 - Which forecasting is better for a specific inventory policy

97 - Introduction.mp4

02:15

98 - Forecasting demonstraion.mp4

11:07

99 - Max Policy.mp4

03:21

100 - Preparing the notebook.mp4

04:50

100 - inventory-with-forecasting-not-solved.zip

101 - Preparing for forecasting.mp4

07:45

102 - Forecasting our first sku.mp4

11:16

103 - Forecasting all SKUs.mp4

09:15

103 - data-forecast.xlsx

104 - MaxpolicyDynamic.mp4

12:27

105 - Inventory Comparison between KNN and ARIMA.mp4

11:20

106 - Assigning cycle service level and preparing for simulation.mp4

08:51

107 - Running the simulation.mp4

11:07

108 - Which forecast is better in terms of inventory.mp4

07:14

108 - inventory-with-forecasting-not-solved.zip

8 - Seasonal Inventory

109 - Intro.mp4

05:10

110 - Seasonal Products.mp4

08:38

111 - Point of Maximum profit.mp4

07:13

112 - How much I will sell.mp4

01:23

113 - Dataable.mp4

05:26

114 - Critical ratio.mp4

04:48

115 - Critical ratio in excel.mp4

09:11

116 - Whats actually happening.mp4

01:47

117 - Critical ratio in python.mp4

09:14

117 - retail-clean.csv.zip

117 - section17.zip

118 - Preparing the data for MPN.mp4

08:16

119 - Creating margin of error.mp4

04:30

120 - Applying MPN on all data.mp4

08:43

121 - Conclusion.mp4

03:39

122 - Seasonal inventory summary.mp4

02:52

123 - Assignment solution.mp4

01:10

123 - seasonal-inventory-answer.zip

123 - seasonal-inventory-question.docx

124 - Seasonal inventory answer.mp4

04:25

125 - Markdown model by JWalker.mp4

10:25

126 - Markdown model in python.mp4

05:39

127 - Final note.mp4

00:49

Description

Apply the Best forecasting model and inventory policy for all the Products in your Assortment and much more!!

What You'll Learn?

Apply EOQ policies with discount , promotions , multiple suppliers and multiple products.
Simulate inventory policies for unlimited number of products.
Know which forecasting is better for your products.
Know which inventory policy is better for your products.
understand the impact of aggregation and dis-aggregation on inventory.
Understand How inventory interact with demand
Work with the specialized inventory library in python Inventorize.
apply markdowns on seasonal products to move inventory
Manage inventory for seasonal products..

Who is this for?

Inventory Managers

Supply chain managers

Buyers

Demand planners

Supply planners

Retail planners

What You Need to Know?

Anaconda (How to install inside)

Microsoft Excel

More details

Description

Manage inventory effortlessly from A-Z

Hi :)
I am Haytham a consultant, a teacher, and a supply chain solutions provider. welcome to my course.

The course has two quizzes and a lot of Excel/Python practice on real inventory cases.
With the ever-increasing reliance on supply chain management to deliver. supply chain jobs become one of the highest in-demand jobs of the twenty-first century, It is one of the jobs that will not be affected by automation because of its nature as a critical thinking and resilient profession. And with the procurement function In the supply chain being the heart and soul of feeding the supply chain with product/material, distribution is equally as important because it streamlines the flow of products to the end customer.
we explain analytically and practically the inventory side of the supply chain.
I am excited to share with you this course that talks about inventory in great detail, I can go as far as saying that the applications inside this course are not anywhere as the inventorize package that is developed by me and has more than 60000 downloads thus far is developed by yours truly.
Inventorize package has a lot of functionalities in my daily consulting activities with multi-national retailers and I would love to share its nitty-gritty details with you. Not only this the course discusses the basics and ascends step by step to the more advanced first by Excel and then using Python.
with this course, Based on one student's demand. we take it one step further; we combine Supply chain, DevOps, and Data science to make a comprehensive inventory course for you.
Don't worry If you don't know how to code and are new to Python, an introductory section is included. we learn step by step by applying supply chain analysis!
NOTE: Full course includes downloadable resources* and *Python project files, Setup Codes, lifetime access**, and a* 30-day money-back guarantee.

In this course we will get to know the following:
1- Types of inventory, EOQ and its variations, and how to calculate inventory costs. (Excel)
2- Inventory KPIs and how toÂ force an inventory policy with a desired fill rate/service level. (Excel)
3-Â Aggregation and disaggregation affect inventory. (Excel)
4- Python crash chapters if you do not know Python.
5- Create an EOQ program in Python.
6- Assigning desired fill rate with Goa seek function (Python).
7- Forecasting in Python.
8- Inventory simulations in Python.
9- Forecasting with inventory simulations in Python.
10- Inventory for seasonal products and how to apply markdowns for them.

Hope you enjoy and happy Supply Chain mining!
Haytham
Rescale Analytics

Feedback from Clients, Training, and other online courses:
"I attended this course with high expectations. And I was not disappointed. ItÂ´s incredible to see what is possible with Python in terms of supply chain planning and optimization. Haytham is doing a great job as a trainer. Starting with an explanation of basics and ending with a presentation of advanced techniques supply chain managers can apply in real life."
Larsen Block
Director Supply Chain Management at Freudenberg Home and Cleaning Solutions GmbH

"In Q4 2018, I was fortunate to find an opportunity to learn R in Dubai, after hearing about it from indirect references in UK.

I attended a Supply Chain Forecasting & Demand Planning Masterclass conducted by Haitham Omar and the possibilities seemed endless. So, we requested Haitham to conduct a 5-day workshop in our office to train 8 staff members, which opened us up as a team to deeper data analysis. Today, we have gone a step further and retained Haitham, as a consultant, to take our data analysis to the next level and to help us implement inventory guidelines for our business. The above progression of our actions is a clear indication of the capabilities of Haitham as a specialist in R and in data analytics, demand planning, and inventory management."

Shailesh Mendonca
Commercial lead-in Adventure AHQ- Sharaf Group

â€œ Haytham mentored me in my Role of Head of Supply Chain efficiency. He is extremely knowledgebase about the supply concepts, latest trends, and benchmarks in the supply chain world. Haythamâ€™s analytics-driven approach was very helpful for me to recommend and implement significant changes to our supply chain at Aster groupâ€
Saify Naqvi
Head of Supply Chain Efficiency

Who this course is for:
Inventory Managers
Supply chain managers
Buyers
Demand planners
Supply planners
Retail planners

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"Never follow a book by its cover, In a world that changes every second, we must be resilient and proactive. " Consultant / Developer /TrainerConsultant in Supply Chain Management & Business IntelligenceFounder - Rescale Analytics – Dubai• PhD student at the University of Bordeaux.• Supply chain and data science consultant for several national and multinational clients in the UAE and France.• Data Scientist, Master of Science in Global Supply Chain Management from Bordeaux Ecole de Management, Bordeaux, FranceHe is currently conducting workshops and seminars in Supply chain and data science as well as consultancy projects for Sephora, Sharaf group and aster pharmacy.• Haytham conducted more than 70 workshops in UAE in the last three years in supply chain and data science. Clients :Sharaf GroupAster GroupSephora FranceDNO Qarar for financial analyticsLamprellNoble ProgPWC training AcademyHigher College of TechnologyPartners: Edusphere dubai- Limar Tech Saudi arabia – sl-tech Abu DhabiProjects :AHQ-SHARAF GROUP:developing an algorithm for the replenishment of stocks to Sharaf group -adventure HQ . the algorithm is being used since November 2019 with notable results.Developing and deploying an algorithm for revenue maximization based on elasticity techniques for adventure zones service provided by AHQ. Projects: Sephora – FranceHaytham is working with Kedge business school as part of the team CSIT for partnership The collaboration of Omni-channel optimization with Sephora France. As a part of his Ph.D. project. Development: Haytham developed the Inventorize package in R mainly used for supply chain analytics with more than 50000 Downloads so far.

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