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Inicio / Cursos / RA: Data Science and Supply Chain analytics. A-Z with Python
Impartido por Haytham Omar-Ph.DPago único de $2,800 MXN · acceso por 12 meses

RA: Data Science and Supply Chain analytics. A-Z with Python

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

Certificado oficial emitido por la SEPA través del Gobierno del Estado de México
12 meses de acceso En línea · 60 h 26 unidades
Qué aprenderás

Lo que serás capaz de hacer

"I attended this course with high expectations. And I was not disappointed. It´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 explanation of basics and ending with 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 New update : Forecast for OTB calculation with AutoML is added (Aug 2023) After our Data Science and supply chain analytics with R course being dubbed the highest rated course in supply chain on Udemy, we are pleased to Introduce Data Science and supply chain analytics. A-Z with Python !! " 60000 Professionals are using inventorize across R & Python. Know how to use it only in this course" It's been seven years since I moved from Excel to data science and since then I have never looked back! With eleven years between working in Procurement, lecturing in universities, training over 70000 professionals in supply chain and data science with R and python , and finally opening my own business in consulting for five years now. I am extremely excited to share with you this course and learn with you through this unique rewarding course. My goal is that all of you become experts in data science and supply-chain . I have put all the techniques I have learned and practiced in this one sweet bundle of data science and supply chain. As a consultancy, we develop algorithms for retailers and supply chains to make aggregate and item controllable forecasting, optimize stocks, plan assortment and Maximize profit margin by optimizing prices . 20000 people are already using our free package for supply chain analysis "Inventorize" and we can't wait to share its capabilities with you so you can start dissecting supply chain problems...for free! The motivation behind this project is filling the gap of finding a comprehensive course that tackles supply chains using data science. there are courses for data science, forecasting, revenue management, inventory management, and simulation modeling. but here we tackle all of them as a bundle. Lectures, Concepts, codes, exercises, and spreadsheets . and we don't present the code, we do the code with you, step by step . the abundance of the data from customers, suppliers, products, and transactions have opened the way for making informed business decisions on a bigger and more dynamic scale that can no longer be achieved by spreadsheets. In this course, we learn data science from a supply chain mindset. Don't worry If you don't know how to code, we learn step by step by applying supply chain analysis! *NOTE: Full course includes downloadable resources and Python project files , homework and course quizzes , lifetime access , and a 30-day money-back guarantee . Who this course is for: · If you are an absolute beginner at coding , then take this course. · If you work in a supply-chain and want to make data-driven decisions , this course will equip you with what you need. · If you are an inventory manager and want to optimize inventory for 1000000 products at once, then this course is for you. · If you work in finance and want to forecast your budget by taking trends, seasonality, and other factors into account then this course is just what you need. · If you are a seasoned python user, then take this course to get up to speed quickly with python capabilities. You will become a regular python user in no time. · If you want to take a deep dive (not just talking) in supply chain management, then take this course. · If you want to apply machine learning techniques for supply -chain , we will walk you through the methods of supervised and unsupervised learning. · If you are switching from Excel to a data science language . then this course 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 course is for you. · If you are frustrated about the limitations of data loading and available modules in excel , then Moving to python will make our lives a whole lot easier. Course Design the course is designed as experiential learning Modules , the first couple of modules are for supply chain fundamentals followed by Python programming fundamentals , this is to level all of the takers of this course to the same pace. and the third part is supply chain applications using Data science which is using the knowledge of the first two modules to apply. while the course 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 supply chain use cases. Supply chain Fundamentals Module includes: 1- Introduction to supply chain. 2- Supply chain Flows. 3- Data produced by supply chains. Python Programming Fundamentals Module includes: 1- Basics of Python 2- Data cleaning and Manipulation. 3- Statistical analysis. 4- Data Visualization. 5- Advanced Programming. Supply chain Applications Module include : 1- Product segmentations single and Multi-criteria. 2- Supplier segmentations. 3- Customers segmentations. 4- Forecasting techniques and accuracy testing. 5- Linear Programming and logistics optimizations. 6- Pricing and Markdowns optimization Techniques. 7- Inventory Policy and Safety stock Calculations. 8- Inventory simulations. 9- Machine Learning for supply-chain. 10- Simulations for optimizing Capacity and Resources. *NOTE: Many of the concepts and analysis I explain first in excel as I find excel the best way to first explain a concept and then we scale up, improve and generalize with Python. By the end of this course, you will have an exciting set of skills and a toolbox you can always rely on when tackling supply chain challenges . The course may take from 12-16 weeks to finish, 4-5 hours of lectures, and practice every week. Happy Supply Chain mining! Haytham Rescale Analytics Feedback from Clients and Training: "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 “ 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. Haytham’s analytics-driven approach was very helpful for me to recommend and implement significant changes to our supply chain at Aster group” Saify Naqvi Head of Supply Chain Efficiency “I participated in the training session called "Supply Chain Forecasting & Management" on December 22nd 2018. This training helped me a lot in my daily work since I am working in Purchase Dpt. Haytham have the pedagogy to explain us very difficult calculations and formula in a simple way. I highly recommend this training.” Djamel BOUREMIZ Purchasing Manager at Mineral Circles Bearings

  • A-Z Guide to Mastering Python for Data Science.
  • Work as A demand Planner.
  • Become a data driven supply chain manager.
  • Use linear Programming in python for logistics optimization and Production scheduling.
  • Set stock policies and safety stocks for all of your Business products.
  • Revenue management

Temario

UNIDAD 1 - Introduction · 11 lecciones

UNIDAD 1 - Introduction

  • IntroVideo · 2 min
  • Why we need to learn coding?Video · 4 min
  • CurriculumVideo · 4 min
  • Plan of attackVideo · 2 min
  • Supply chain visualizationVideo · 8 min
  • Cost and service DynamicsVideo · 5 min
  • Service level and product characteristicsVideo · 7 min
  • Customer and supplier characteristicsVideo · 9 min
  • Supply chain ViewsVideo · 12 min
  • The Financial flowVideo · 3 min
  • Why is supply chain complicatedVideo · 7 min
UNIDAD 2 - Supply chain Data · 8 lecciones

UNIDAD 2 - Supply chain Data

  • introVideo · 1 min
  • Types of Data in supply chainVideo · 14 min
  • Data From suppliersVideo · 3 min
  • Data from productionVideo · 2 min
  • Data from stocksVideo · 2 min
  • Data from sales and customersVideo · 7 min
  • Why we need to learn Data ScienceVideo · 5 min
  • Analytics TypesVideo · 5 min
UNIDAD 3 - Welcome to the world of Python · 7 lecciones

UNIDAD 3 - Welcome to the world of Python

  • PythonVideo · 3 min
  • downloading AnacondaVideo · 2 min
  • Installing AnacondaVideo · 1 min
  • Spyder overviewVideo · 12 min
  • Jupiter Notebook overviewVideo · 3 min
  • Python LibrariesVideo · 6 min
  • Inventorize PackageVideo · 1 min
UNIDAD 4 - Python Programming Fundamentals · 19 lecciones

UNIDAD 4 - Python Programming Fundamentals

  • IntroVideo · 7 min
  • DataframesVideo · 3 min
  • Arithmetic Calculations with PythonVideo · 8 min
  • ListsVideo · 7 min
  • DictionariesVideo · 5 min
  • ArraysVideo · 3 min
  • Importing data in PythonVideo · 8 min
  • Subsetting Data FramesVideo · 9 min
  • ConditionsVideo · 4 min
  • Writing functionsVideo · 8 min
  • mappingVideo · 2 min
  • for loopsVideo · 2 min
  • for looping a functionVideo · 4 min
  • Mapping On a data frameVideo · 6 min
  • for looping on a data frameVideo · 8 min
  • SummaryVideo · 9 min
  • AssignmentVideo · 2 min
  • Assignment answer 1Video · 6 min
  • Assignment answer 2Video · 10 min
UNIDAD 5 - Supply chain statistical analysis · 28 lecciones

UNIDAD 5 - Supply chain statistical analysis

  • IntroVideo · 3 min
  • Measures of centrality and SpreadVideo · 6 min
  • Calculating the meanVideo · 5 min
  • Calculating the medianVideo · 2 min
  • Measures of spreadVideo · 5 min
  • PercentilesVideo · 2 min
  • Correlations: subsetting Cars datasetVideo · 6 min
  • Correlations of continuous variablesVideo · 9 min
  • Correlation plotsVideo · 5 min
  • Correlation thresholdsVideo · 2 min
  • Detecting outliersVideo · 4 min
  • Outliers in pythonVideo · 7 min
  • linear regressionVideo · 5 min
  • intro to linear regressionVideo · 9 min
  • Linear Regression in pythonVideo · 3 min
  • Fitting the linear modelVideo · 7 min
  • Importance of distributions in supply chainVideo · 12 min
  • Chi- Square testsVideo · 3 min
  • Distributions in ExcelVideo · 8 min
  • Distributions Chi-square testsVideo · 7 min
  • cover for 90% of demandVideo · 5 min
  • AssignmentVideo · 1 min
  • Assignment AnswerVideo · 8 min
  • Distributions in pythonVideo · 5 min
  • Testing for several distributionsVideo · 9 min
  • SummaryVideo · 1 min
  • AssignmentVideo · 1 min
  • Assignment answerVideo · 6 min
UNIDAD 6 - Manipulation and Data cleaning · 27 lecciones

UNIDAD 6 - Manipulation and Data cleaning

  • Manipulation IntroVideo · 2 min
  • Dropping Duplicates and NAsVideo · 7 min
  • Conversions lectureVideo · 4 min
  • ConversionsVideo · 5 min
  • FilterationsVideo · 8 min
  • ImputationsVideo · 5 min
  • Indexing tutorialVideo · 4 min
  • slicing indexVideo · 4 min
  • Manipulation LectureVideo · 5 min
  • GroupbyVideo · 7 min
  • Slicing the group byVideo · 5 min
  • Dropping levelsVideo · 2 min
  • The proper formVideo · 4 min
  • Pivot TablesVideo · 8 min
  • Aggregate function in pivot tableVideo · 6 min
  • Melting the dataVideo · 6 min
  • Left JoinVideo · 4 min
  • inner and outer joinVideo · 4 min
  • Joining in pythonVideo · 4 min
  • Inner, left join and full join (outer)Video · 6 min
  • SummaryVideo · 2 min
  • AssignmentVideo · 2 min
  • Assignment answer 1Video · 6 min
  • Assignment answer 2Video · 6 min
  • Assignment answer 3Video · 8 min
  • Assignment answer 4Video · 7 min
  • Assignment answer 5Video · 14 min
UNIDAD 7 - Working with dates in Python · 13 lecciones

UNIDAD 7 - Working with dates in Python

  • Date IntroVideo · 7 min
  • datetimeVideo · 9 min
  • Last purchase date and recencyVideo · 9 min
  • recency HistogramVideo · 2 min
  • Modeling inter-arrival timeVideo · 8 min
  • Modeling inter_arrival time 2Video · 6 min
  • Modeling inter arrival time 3Video · 5 min
  • ResamplingVideo · 10 min
  • rolling time seriesVideo · 3 min
  • rolling Time series 2Video · 3 min
  • SummaryVideo · 5 min
  • AssignmentVideo · 2 min
  • Assignment AnswerVideo · 10 min
UNIDAD 8 - Visualization with matplotlib and seaborn · 14 lecciones

UNIDAD 8 - Visualization with matplotlib and seaborn

  • IntroVideo · 4 min
  • Line plotVideo · 5 min
  • Line Plot part 2Video · 7 min
  • scatter plotVideo · 8 min
  • CountplotVideo · 5 min
  • BarplotVideo · 13 min
  • Distribution PlotsVideo · 6 min
  • BoxplotsVideo · 6 min
  • HistogramsVideo · 3 min
  • PairplotsVideo · 7 min
  • Visualization SummaryVideo · 1 min
  • AssignmentVideo · 3 min
  • Assignment answer 1Video · 2 min
  • Assignment Answer 2Video · 5 min
UNIDAD 9 - Segmentation · 18 lecciones

UNIDAD 9 - Segmentation

  • IntroVideo · 6 min
  • Pareto LawVideo · 7 min
  • Importance of ABC analysisVideo · 6 min
  • Multi-criteria segmentationVideo · 5 min
  • Transforming the data for excelVideo · 12 min
  • ABC_analysis in ExcelVideo · 10 min
  • AssignmentVideo · 2 min
  • ABC in pythonVideo · 5 min
  • Multi-Criteria ABC analysisVideo · 5 min
  • Multi-Criteria ABC analysis with store or department levelVideo · 12 min
  • Supplier segmentation 1Video · 7 min
  • Supplier segmentation 2Video · 5 min
  • Supplier Segmentation In pythonVideo · 7 min
  • Value_indexVideo · 2 min
  • Visualizing KrajicVideo · 9 min
  • SummaryVideo · 7 min
  • Assignment ABCVideo · 1 min
  • Assignment answerVideo · 12 min
UNIDAD 10 - Forecasting Basics · 16 lecciones

UNIDAD 10 - Forecasting Basics

  • Why we need forecastsVideo · 4 min
  • Qualitative and Quantitative ForecastingVideo · 4 min
  • Optimistic and Pessimistic ForecastingVideo · 4 min
  • Time ComponentsVideo · 5 min
  • Preparing the Data for RegressionVideo · 5 min
  • Forecasting in ExcelVideo · 12 min
  • Forecasting in excel 2Video · 10 min
  • AssignmentVideo · 2 min
  • Regression in pythonVideo · 9 min
  • Regression in python part2Video · 6 min
  • Initializing a date range for forecastingVideo · 5 min
  • ForecastingVideo · 8 min
  • SummaryVideo · 2 min
  • Assignment QuestionsVideo · 1 min
  • AssignmentVideo · 5 min
  • Assignment2Video · 1 min
UNIDAD 11 - Time-Series Modeling · 25 lecciones

UNIDAD 11 - Time-Series Modeling

  • Time Series IntroVideo · 6 min
  • Accuracy MeasuresVideo · 2 min
  • Preparing the data for time-seriesVideo · 7 min
  • Getting the time series components: LectureVideo · 3 min
  • Getting the time series componentsVideo · 1 min
  • components usesVideo · 5 min
  • Arima ModelsVideo · 9 min
  • Stationarity test in pythonVideo · 7 min
  • Arima in pythonVideo · 12 min
  • ARIMA diagnosticsVideo · 2 min
  • Grid searchVideo · 6 min
  • For looping ARIMAVideo · 10 min
  • error handlingVideo · 7 min
  • fitting the best modelVideo · 4 min
  • Mean absolute errorVideo · 4 min
  • Arima ComparisonVideo · 4 min
  • Exponential smoothingVideo · 4 min
  • Exponential smoothing in pythonVideo · 8 min
  • Comparing exponential smoothing modelsVideo · 7 min
  • Time series summaryVideo · 3 min
  • Assignment.Video · 3 min
  • Assignment Explanation 1Video · 4 min
  • assignment explanation 2Video · 4 min
  • Assignment explanation 3Video · 3 min
  • Assignment Explanation 4Video · 2 min
UNIDAD 12 - Forecasting Segmentation · 13 lecciones

UNIDAD 12 - Forecasting Segmentation

  • Product ClassficationsVideo · 5 min
  • Demand ClassificationVideo · 6 min
  • HolidaysVideo · 4 min
  • Coefficient of Variation SquaredVideo · 7 min
  • Preparing for Average Demand intervalVideo · 5 min
  • Average Demand intervalVideo · 5 min
  • DurationsVideo · 3 min
  • Coerce DurationsVideo · 3 min
  • ClassificationsVideo · 9 min
  • ConclusionVideo · 6 min
  • SummaryVideo · 3 min
  • AssignmentVideo · 2 min
  • Assignment ExplanationVideo · 7 min
UNIDAD 13 - Supply chain simulations · 21 lecciones

UNIDAD 13 - Supply chain simulations

  • IntroductionVideo · 6 min
  • Important update to this sectionLectura · 0 min
  • Waiting linesVideo · 7 min
  • Simulation Example DemoVideo · 1 min
  • Simulation ExcelVideo · 9 min
  • Simulation AssignmentVideo · 1 min
  • Simulating waiting time in PythonVideo · 10 min
  • 1000 simulationsVideo · 5 min
  • Downloading RVideo · 3 min
  • Installing RVideo · 4 min
  • Installing Rpy2Video · 4 min
  • Simulation with queue ComputerVideo · 10 min
  • Multiple_resourcesVideo · 11 min
  • Getting the optimum number of serversVideo · 6 min
  • Capacity_constrainsVideo · 11 min
  • Multiple service lectureVideo · 5 min
  • Multiple service with queue computerVideo · 9 min
  • Mean waiting time of the systemVideo · 16 min
  • SummaryVideo · 2 min
  • AssignmentVideo · 2 min
  • Assignment ExplanationVideo · 9 min
UNIDAD 14 - Linear Programing in python · 22 lecciones

UNIDAD 14 - Linear Programing in python

  • Optimization introVideo · 7 min
  • Problem FormulationVideo · 9 min
  • Model in ExcelVideo · 10 min
  • Installing PulpVideo · 1 min
  • Model In PythonVideo · 10 min
  • AssignmentVideo · 1 min
  • Assignment ExplanationVideo · 3 min
  • Transport Problem in Excel Part 1Video · 10 min
  • Transport Problem in in Pulp Part 1Video · 8 min
  • Transport Optimization Part 2Video · 8 min
  • Formulating supply constraintVideo · 5 min
  • Solving the modelVideo · 6 min
  • AssignmentVideo · 1 min
  • Assignment answerVideo · 4 min
  • Production planningVideo · 4 min
  • Production schedulingVideo · 8 min
  • Production scheduling in PythonVideo · 6 min
  • Constraints DefinitionVideo · 8 min
  • Model SensitivityVideo · 3 min
  • SummaryVideo · 1 min
  • Production scheduling assignmentVideo · 1 min
  • Assignment ExplanationVideo · 6 min
UNIDAD 15 - Inventory · 17 lecciones

UNIDAD 15 - Inventory

  • InroVideo · 5 min
  • Why we need inventory?Video · 10 min
  • Inventory StrategiesVideo · 7 min
  • Inventory Types and EOQVideo · 9 min
  • Total Logistics Cost and total relevant costVideo · 6 min
  • Economic Order Quantity with Excel.Video · 4 min
  • EOQ with discountsVideo · 5 min
  • EOQ SensitivityVideo · 8 min
  • EOQ in PythonVideo · 8 min
  • EOQ practicalVideo · 4 min
  • EOQ with lead-timeVideo · 5 min
  • EOQ with Lead-time in pythonVideo · 7 min
  • SummaryVideo · 2 min
  • Summary part 2Video · 2 min
  • AssignmentVideo · 2 min
  • Assignment Answer1Video · 3 min
  • Assignment Answer 2Video · 3 min
UNIDAD 16 - Inventory With uncertainty · 16 lecciones

UNIDAD 16 - Inventory With uncertainty

  • IntroVideo · 8 min
  • Variability In supply chainVideo · 4 min
  • Demand Lead-time and Sigma Demand Lead-timeVideo · 4 min
  • Calculating average daily demandVideo · 5 min
  • Method 1 for safety stock calculationVideo · 9 min
  • Method 2 for safety stock calculationVideo · 8 min
  • Preparing the Data for safety stock calculationsVideo · 6 min
  • Calculating average and standard deviation Per SKUVideo · 8 min
  • Segmentation of data for service levelVideo · 8 min
  • Reorder point for All SkusVideo · 15 min
  • Reorder Point ConclusionVideo · 9 min
  • leadtime variabilityVideo · 6 min
  • Lead time variability in PythonVideo · 1 min
  • SummaryVideo · 5 min
  • AssignmentVideo · 2 min
  • Assiignment EplanationVideo · 9 min
UNIDAD 17 - Inventory Simulations · 25 lecciones

UNIDAD 17 - Inventory Simulations

  • Inventory PoliciesVideo · 2 min
  • Inventory PoliciesVideo · 9 min
  • Min Q DemonstrationVideo · 5 min
  • Min Q LectureVideo · 3 min
  • Min Q in ExcelVideo · 6 min
  • Periodic Review DemonstrationVideo · 8 min
  • Periodic Review LectureVideo · 4 min
  • Periodic Review Demonstration in ExcelVideo · 5 min
  • Min Max DemonstrationVideo · 4 min
  • Min Max LectureVideo · 4 min
  • Min Max example in excelVideo · 5 min
  • Base stock DemonstrationVideo · 4 min
  • Base stock policyVideo · 4 min
  • Base stock Policy in excelVideo · 4 min
  • AssignmentVideo · 2 min
  • S,Q policy in PythonVideo · 13 min
  • Min Max PolicyVideo · 5 min
  • Min Max simulationVideo · 2 min
  • Periodic Policy in PythonVideo · 5 min
  • Hibrid PolicyVideo · 9 min
  • Base Stock PolicyVideo · 6 min
  • Comparing all policiesVideo · 7 min
  • SummaryVideo · 4 min
  • Inventory simulations assignmentVideo · 1 min
  • Inventory simulation assignmentVideo · 6 min
UNIDAD 18 - Seasonal Inventory · 16 lecciones

UNIDAD 18 - Seasonal Inventory

  • IntroVideo · 5 min
  • Seasonal ProductsVideo · 9 min
  • Point of Maximum ProfitVideo · 7 min
  • How Much I will sell?Video · 1 min
  • Data TableVideo · 5 min
  • Critical RatioVideo · 5 min
  • Critical Ratio in ExcelVideo · 9 min
  • What's actually happening?Video · 2 min
  • Critical Ratio in pythonVideo · 9 min
  • Preparing the Data for MPNVideo · 8 min
  • Creating a Margin of errorVideo · 4 min
  • Applying MPN on all dataVideo · 9 min
  • ConclusionVideo · 4 min
  • Seasonal Inventory SummaryVideo · 3 min
  • Assignment solutionVideo · 1 min
  • Seasonal inventory answerVideo · 4 min
UNIDAD 19 - Consumer Behavior and pricing · 23 lecciones

UNIDAD 19 - Consumer Behavior and pricing

  • Introduction.Video · 3 min
  • Pricing History.Video · 5 min
  • Why Pricing is important?Video · 5 min
  • Customers Perception of Price.Video · 6 min
  • Pricing MechanismsVideo · 4 min
  • CommodotiesVideo · 2 min
  • Price response functionVideo · 5 min
  • Price response function motivation in pythonVideo · 4 min
  • Simulating the DemandVideo · 6 min
  • Point of Maximum ProfitVideo · 7 min
  • AssignmentVideo · 1 min
  • Assignment explanationVideo · 5 min
  • Elasticity IntroVideo · 5 min
  • ElasticityVideo · 8 min
  • Linear Elasticity with InventorizeVideo · 3 min
  • Parsing DatesVideo · 4 min
  • Getting list of unique SkusVideo · 5 min
  • For looping Linear ElasticityVideo · 7 min
  • Error Handling for linear elasticityVideo · 5 min
  • ConclusionVideo · 5 min
  • Single Optimization SummaryVideo · 3 min
  • AssignmentVideo · 1 min
  • ExplanationVideo · 3 min
UNIDAD 20 - Logit price response function · 7 lecciones

UNIDAD 20 - Logit price response function

  • IntroVideo · 5 min
  • Logistic RégressionVideo · 7 min
  • Logistic modeling with inventorizeVideo · 6 min
  • Comparison between logistic and linearVideo · 6 min
  • Logit For loopingVideo · 6 min
  • Logit assignmentVideo · 1 min
  • Logit Assignment answerVideo · 5 min
UNIDAD 21 - Multi Product Optimization · 8 lecciones

UNIDAD 21 - Multi Product Optimization

  • IntroductionVideo · 6 min
  • Competing ProductsVideo · 4 min
  • Relation among ProductsVideo · 3 min
  • Multi-Variate regression in pythonVideo · 11 min
  • Multinomial Choice ModelsVideo · 5 min
  • Multinomial Logit ModelsVideo · 5 min
  • Multi Competing products in pythonVideo · 5 min
  • SummaryVideo · 2 min
UNIDAD 22 - Markdowns · 12 lecciones

UNIDAD 22 - Markdowns

  • IntroVideo · 5 min
  • MarkdownsVideo · 5 min
  • Why we do markdownsVideo · 5 min
  • Customers segment to markdownsVideo · 3 min
  • Problem formulationVideo · 4 min
  • Markdowns for multiple periodsVideo · 7 min
  • Setting up solverVideo · 2 min
  • Salvage ValueVideo · 1 min
  • Markdowns with forecasting.Video · 3 min
  • Sensitivity analysis.Video · 4 min
  • Markdowns for one periodVideo · 2 min
  • AssignmentVideo · 1 min
UNIDAD 23 - RFM analysis · 8 lecciones

UNIDAD 23 - RFM analysis

  • RFM analysisVideo · 4 min
  • Customer Segmentation based on RFM.Video · 4 min
  • Customer Recency in PythonVideo · 8 min
  • Frequency and Monetary ValueVideo · 7 min
  • RankingVideo · 7 min
  • GroupingVideo · 8 min
  • Creating the categoriesVideo · 3 min
  • ConclusionVideo · 5 min
UNIDAD 24 - Machine Learning · 33 lecciones

UNIDAD 24 - Machine Learning

  • IntroVideo · 5 min
  • Decision Tree DemoVideo · 9 min
  • OverfittingVideo · 3 min
  • Kmeans in PythonVideo · 7 min
  • Centroids VisualizationVideo · 3 min
  • Elbow SpreeVideo · 7 min
  • Preparing the data for regressionVideo · 7 min
  • Getting the time ComponentsVideo · 9 min
  • one hot encodingVideo · 10 min
  • Training the modelsVideo · 8 min
  • KNNVideo · 4 min
  • KNN Grid SearchVideo · 11 min
  • Lasso Grid SearchVideo · 8 min
  • Regularization Importance in LassoVideo · 8 min
  • Regularization VisualizationVideo · 3 min
  • Classification Problem orientationVideo · 2 min
  • Exploring the banking dataVideo · 12 min
  • Preparing the DataVideo · 11 min
  • Logistic Regression without Grid SearchVideo · 6 min
  • Pre-Processing of DataVideo · 6 min
  • Grid SearchVideo · 11 min
  • Confusion MatrixVideo · 9 min
  • AUCVideo · 9 min
  • Plotting AUCVideo · 3 min
  • Preparing for PipelinesVideo · 7 min
  • Pipelines for four modelsVideo · 6 min
  • Grid For Logistic RegressionVideo · 5 min
  • GridsVideo · 5 min
  • For looping PipelinesVideo · 8 min
  • VerboseVideo · 3 min
  • Pipeline conclusionVideo · 1 min
  • Random forest and decision tree comparisonVideo · 6 min
  • Randomized SearchVideo · 7 min
UNIDAD 25 - Forecasting-OTB-AutoML Problem- Advanced manipulation with Pandas and Pycaret · 18 lecciones

UNIDAD 25 - Forecasting-OTB-AutoML Problem- Advanced manipulation with Pandas and Pycaret

  • Orientation to usecaseVideo · 5 min
  • Data DescriptionVideo · 6 min
  • Importing DataVideo · 8 min
  • Transforming the data to monthlyVideo · 8 min
  • Getting seasonality featureVideo · 10 min
  • Generating Coherent Time-seriesVideo · 12 min
  • Getting back old dataVideo · 10 min
  • Groupby & TransformVideo · 9 min
  • Trend and SeasonalityVideo · 5 min
  • Generating time-series features 1Video · 5 min
  • Generating Time-series features 2Video · 8 min
  • Imputing all columns at onceVideo · 8 min
  • Splitting the historyVideo · 11 min
  • Running the experiment and comparing modelsVideo · 7 min
  • Creating models and tuningVideo · 7 min
  • blending & StackingVideo · 8 min
  • PredictionVideo · 8 min
  • Visualization and ConclusionVideo · 9 min
UNIDAD 26 - Keip · 2 lecciones

UNIDAD 26 - Keip

  • What is Keip ?Video · 2 min
  • PitchdeckVideo · 0 min
Certificado oficial

Tu certificado lo emite la SEP, no solo una plataforma

Al demostrar la competencia recibes un certificado emitido por la Secretaría de Educación Pública a través del Gobierno del Estado de México: un documento oficial que puedes presentar con confianza ante cualquier empleador o institución.

Tu certificado con INEC

  • Lo emite la Secretaría de Educación Pública (SEP), a través del Gobierno del Estado de México
  • Documento oficial con folio verificable en línea
  • Lo otorga la Universidad Tecnológica Fidel Velázquez

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  • Constancia privada emitida por la misma plataforma
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Tu itinerario, de la inscripción al certificado

  1. 1

    Inscripción con pago único

    Pagas $2,800 MXN una sola vez y entras de inmediato al curso.

  2. 2

    Estudias a tu ritmo

    26 unidades con videos, lecturas y actividades, disponibles 24/7 durante 12 meses.

  3. 3

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    Cuestionarios para comprobar lo aprendido.

  4. 4

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Lo que obtienes

Un certificado oficial de la SEP

Muestra del certificado: RA: Data Science and Supply Chain analytics. A-Z with Python

Muestra · verificable por folio y QR

  • Emitido por la Secretaría de Educación Pública (SEP), a través del Gobierno del Estado de México. No es una constancia privada: es un documento oficial, y ese respaldo marca la diferencia frente a otras plataformas en línea.
  • Contenido impartido por Haytham Omar-Ph.D.
  • Folio y QR verificables para compartirlo con quien te contrate.
Medios que necesitas
Equipo de cómputo Conexión estable a internet
Pago único

Empieza hoy, a tu ritmo

Un solo pago y acceso inmediato al curso completo durante 12 meses.

  • 26 unidades · 427 lecciones · 60 h
  • 12 meses de acceso
  • Certificado emitido por la SEP (Gob. del Estado de México) con folio verificable
Pago único
$2,800MXN
Acceso por 12 meses
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Preguntas frecuentes

Sobre tu inscripción

¿Cómo es el pago?

Un solo pago de $2,800 MXN. No hay mensualidades ni cargos recurrentes.

¿Cuánto tiempo tengo acceso?

12 meses desde tu inscripción, 24/7, para avanzar a tu ritmo.

¿Quién imparte el contenido?

El curso es impartido por Haytham Omar-Ph.D; INEC gestiona tu inscripción, evaluación y certificado.

¿Qué pasa cuando vence mi acceso?

Puedes renovar tu cuenta tú mismo desde la plataforma, sin trámites ni esperas.

Certificado emitido por la SEP a través del Gobierno del Estado de México · RA: Data Science and Supply Chain analytics. A-Z with Python

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