RA: Retail Management, Analytics with Excel & Python. from Udemy

"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.

What's inside

Learning objectives

Become a retail expert planner!
Learn python
Retail management
Deep learning
Pricing

Forecasting
Pandas
Retail analytics
Visual merchandising

Become a retail expert planner!
Learn python
Retail management
Deep learning
Pricing
Forecasting
Pandas
Retail analytics
Visual merchandising

Syllabus

Linear Regrression

Retail Fundmentals

Curriculum summary

Curriculum Layout

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Uses Python and Excel, which are both widely used for data analysis and accessible to learners with varying levels of technical expertise

Covers retail fundamentals, which provides a strong foundation for learners new to the retail industry and those looking to formalize their knowledge

Includes hands-on coding sessions and real retail use cases, which allows learners to apply their knowledge and develop practical skills

Explores deep learning and regression techniques, which are valuable tools for forecasting and optimizing retail operations

Requires downloading and installing Anaconda, which may pose a barrier for some learners with limited technical skills or older computers

Focuses on applying data science to retail, which may not be relevant to learners interested in general data science applications

Reviews summary

Retail analytics with excel and python

According to learners, this course offers a solid introduction to retail fundamentals and data analytics using Excel and Python. Students appreciate that it caters to absolute beginners in coding, providing a step-by-step approach to Python basics and data manipulation using Pandas. The course is seen as practical, incorporating real retail use cases for practice and assessments. While the course covers a range of topics including forecasting and pricing, some reviewers feel the sections on advanced topics like deep learning are brief or rushed, and suggest that supplementary learning is needed for deeper understanding. Overall, it's considered a great starting point for applying data science concepts in a retail context.

Provides a base in retail & Python.

"the first couple of modules are for retail fundamentals followed by Python programming fundamentals."

"This course provided me with a strong foundation in using Python for data analysis..."

"Gained a solid understanding of core retail concepts before diving into analytics."

"The introduction to Pandas and data manipulation was thorough for a beginner."

Focuses on real retail problems.

"all the practice and assessments are real retail use cases."

"Learned practical tools and strategies that I could apply immediately to my work."

"The application of concepts to retail scenarios using Python was very helpful."

"Liked how the course tied data analysis directly to retail management decisions."

Great for those new to coding or retail.

"If you are an absolute beginner at coding, then take this Program."

"Don't worry If you don't know how to code, we learn step by step by applying retail analysis."

"It's a great course for beginners in retail looking to understand analytics."

"I had no prior coding experience, and the Python sections were easy to follow."

May need external resources.

"for more deep understanding need to do more practice and get more resources for retail analytics."

"While a great start, I needed to look up additional information on some topics."

"Felt the need for supplementary materials to fully grasp certain concepts."

"Could use more in-depth coverage on complex topics..."

Deep learning section lacks depth.

"Forecasting In python with Deep learning and regression techniques, ANN and RNN."

"The deep learning part felt a bit rushed and could use more detail."

"Requires additional study for the more advanced forecasting models presented."

"Wish there was more explanation on the ANN/RNN sections."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in RA: Retail Management, Analytics with Excel & Python. with these activities:

Review Retail Fundamentals

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Solidify your understanding of core retail concepts before diving into analytics. This will provide a strong foundation for applying data-driven techniques.

Browse courses on Retail

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Review definitions of retail types and formats.
Summarize the key components of the retail value chain.
Practice identifying different category roles and strategies.

Brush Up on Excel Skills

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Practice essential Excel functions to prepare for forecasting and pricing analysis. This will make it easier to follow along with the Excel-based sections of the course.

Browse courses on Excel

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Practice using formulas for calculations and data manipulation.
Review how to create charts and graphs for data visualization.
Familiarize yourself with Excel's solver add-in.

Read 'Retail Management: A Strategic Approach'

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Gain a broader understanding of retail strategy and operations. This will help you apply the analytical techniques learned in the course to real-world retail challenges.

View Retail Management, Global Edition on Amazon

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Read chapters related to merchandising and pricing strategies.
Take notes on key concepts and examples.
Reflect on how these concepts relate to data analysis.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Practice Pandas Data Manipulation

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Reinforce your Pandas skills through targeted exercises. This will improve your efficiency in data cleaning and manipulation tasks within the course.

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Complete Pandas tutorials on data filtering and selection.
Practice using Pandas functions for data aggregation and grouping.
Work through exercises on handling missing data in Pandas.

Read 'Python for Data Analysis'

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Enhance your Python skills for data analysis. This book will provide a deeper understanding of Pandas and other relevant libraries.

View Python for Data Analysis on Amazon

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Read chapters related to Pandas data structures and manipulation.
Work through the examples in the book to practice your skills.
Refer to the book as a reference when working on retail analytics projects.

Analyze a Retail Dataset

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Apply your Python and retail knowledge to a real-world dataset. This will solidify your understanding of the course material and build your portfolio.

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Find a publicly available retail dataset (e.g., from Kaggle).
Use Pandas to clean and explore the data.
Perform basic retail analytics, such as sales forecasting or customer segmentation.
Document your findings in a report or presentation.

Write a Blog Post on Retail Pricing Strategies

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Deepen your understanding of pricing by explaining different strategies in a blog post. This will help you articulate the concepts and reinforce your learning.

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Research different retail pricing strategies (cost-based, value-based, etc.).
Write a blog post explaining each strategy and its pros and cons.
Include examples of how these strategies are used in practice.

Career center

Learners who complete RA: Retail Management, Analytics with Excel & Python. will develop knowledge and skills that may be useful to these careers:

Retail Analyst

A Retail Analyst examines sales data, consumer trends, and market conditions to provide insights that drive business decisions. This course is a strong foundation for this career, as it covers retail fundamentals, manipulation of data with Pandas, and working with Python for analytics. Retail Analysts need to understand the retail environment, including retail formats and fundamentals, which the course covers extensively. Moreover, the course's focus on forecasting with Excel and Python, including deep learning and regression techniques, as well as adjusting product prices to maximize revenue, is directly applicable to the analytical tasks performed by a Retail Analyst. Someone interested in becoming a Retail Analyst should consider this course in particular.

See salaries and explore the career path for Retail Analyst

Pricing Analyst

A Pricing Analyst is primarily responsible for determining optimal pricing strategies to maximize revenue and profitability. This individual analyzes market trends, competitor pricing, and consumer behavior to make data-driven pricing recommendations. This course helps with the Pricing Analyst role by covering the adjustment of product prices to maximize revenue and markdown strategies. The course delves into pricing concepts, including cost-based pricing, value-based pricing, and demand-based pricing. The course's exploration of price response functions, elasticity, and willingness to pay, coupled with practical exercises, makes this course particularly beneficial for aspiring Pricing Analysts. Someone set on becoming a Pricing Analyst should consider this course.

See salaries and explore the career path for Pricing Analyst

Data Scientist

Data Scientists analyze complex datasets to extract meaningful insights and develop predictive models. This course may be useful for a Data Scientist, providing a foundation in retail analytics using Python. The course covers the manipulation of data with Pandas, forecasting with Python using deep learning and regression techniques, and product placement strategies. The program also includes an introduction to Python, data frames, arithmetic calculations, lists, dictionaries, arrays, and importing data in Python. While a Data Scientist typically requires an advanced degree, this course may provide a hands-on introduction to applying data science techniques within the domain of retail.

See salaries and explore the career path for Data Scientist

Market Research Analyst

A Market Research Analyst studies consumer behavior, market trends, and competitor activities to advise companies on marketing and product development strategies. This course includes retail fundamentals and retail analytics, which may be useful for someone in this role. This course includes retail fundamentals, plus using Pandas and Python to conduct an analysis of retail-based data. The understanding of the retail environment and formats that it provides would serve those entering this field well. Aspiring Market Research Analysts who are seeking to study the retail industry may appreciate this course.

See salaries and explore the career path for Market Research Analyst

Business Intelligence Analyst

Business Intelligence Analysts examine data to identify trends and insights that help organizations make better decisions. A core function of a Business Intelligence Analyst is to present data in a meaningful way to stakeholders across an organization. This course may be useful to a Business Intelligence Analyst, as it incorporates retail fundamentals, manipulation of data with Pandas, and working with Python for analytics. This course provides a background in using spreadsheets and Python to conduct an analysis of retail businesses. Since a Business Intelligence Analyst is typically expected to understand multiple kinds of data, the retail focus of this course may be useful for those seeking a Business Intelligence Analyst role in this specific sector.

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Inventory Manager

An Inventory Manager oversees the flow of goods in a retail setting, ensuring adequate stock levels while minimizing waste and storage costs. Inventory management typically involves using analytical skills to forecast trends, estimate demand, and track the progress of items. This course may prove helpful for Inventory Managers, since it covers retail fundamentals, manipulation of data with Pandas, and working with Python for analytics. The focus on forecasting with Excel is especially relevant. This course may be useful to those Inventory Managers seeking to use Python for data management.

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Supply Chain Analyst

A Supply Chain Analyst optimizes the flow of goods from suppliers to consumers, focusing on efficiency, cost reduction, and timely delivery. As a Supply Chain Analyst, you are going to be expected to use analytical skills to support planning, forecasting, and decision-making. This course may be useful for Supply Chain Analysts, since it covers retail fundamentals, manipulation of data with Pandas, and working with Python for analytics. By explaining the retail environment, as well as the use of Python in this context, this course may serve as a general introduction to analytics for Supply Chain Analysts.

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Product Manager

Product Managers guide the strategy, roadmap, and feature definition for a product or product line. Product managers typically work at technology companies, but retail firms also employ product managers. In this context, product managers will need to understand the retail environment. The inclusion of product placement strategies inside the stores may be useful for Product Managers who may be focusing on brick and mortar stores. While the course is not necessarily tailored to Product Managers, the retail analytics component will be applicable.

See salaries and explore the career path for Product Manager

Category Manager

A Category Manager is responsible for the performance of a specific group of products, or category, within a retail organization. The Category Manager must understand retail fundamentals in order to optimize the different components of their business. In this course, learners can understand topics such as retail management, merchandise mix, SKU types, breadth versus width, deep versus shallow assortment, Retailer Brand, and Category Role. Aspiring Category Managers may find that this course provides a useful introduction to the topic.

See salaries and explore the career path for Category Manager

Visual Merchandiser

A Visual Merchandiser creates visually appealing displays in retail stores to attract customers and increase sales. The job relies on an understanding of retail, as well as an understanding of how to use analytics to maximize sales. This course may be useful to a Visual Merchandiser, since it covers retail fundamentals, plus includes a lecture on visual merchandising. Visual Merchandisers should keep in mind that this course is likely to provide an introduction to the topic. Nevertheless, Visual Merchandisers can benefit from the topics taught.

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Retail Operations Manager

A Retail Operations Manager oversees the day-to-day operations of a retail store or chain, ensuring efficiency, customer satisfaction, and profitability. Since a Retail Operations Manager needs to understand the retail environment, this course may be helpful to those who are pursuing this role. In particular, the course goes over the types of retail, merchandise mix, SKU types, category role, and category strategy. This course does not cover all of the duties of a Retail Operations Manager, but it may be a good start for those who wish to enter this field.

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Management Consultant

Management Consultants advise organizations on how to improve their performance and efficiency. This course may be useful to Management Consultants by going over retail fundamentals such as the types of retail, SKU types, category role and strategy, and visual merchandising. A Management Consultant can also leverage the Python skills taught in the course to provide deeper analysis and advice to retail clients. Management Consultants can use these quantitative skills and apply them to their role.

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Business Development Manager

A Business Development Manager focuses on identifying new business opportunities, building strategic partnerships, and expanding market reach for a company. Business Development Managers may find it useful to understand the retail landscape when working with retail clients. Since this course goes over key retail topics, such as the types of retail and the multi-channel environment, it may be useful for a Business Development Manager. The course is not primarily tailored to a Business Development Manager, but it may provide a good introduction to the topic.

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Financial Analyst

A Financial Analyst analyzes financial data, prepares reports, and provides investment recommendations to guide financial decisions. Financial analysts are frequently expected to deeply understand analytics and data analysis. This course includes retail fundamentals, manipulation of data with Pandas, and working with Python for analytics. Even though the course has a retail focus, aspiring Financial Analysts may appreciate learning the basic skills of data analysis here. This may be useful for Financial Analysts who work primarily with retailers.

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Marketing Manager

Marketing Managers plan, direct, and coordinate marketing activities to promote products or services. This course may be useful for a marketing manager who wishes to gain a better understanding of retail businesses. In particular, the course focuses on forecasting and adjusting prices to maximize revenue. This course does not necessarily equip a Marketing Manager with all of the information they need, but it will help them understand key retail analytics concepts, which can then be applied to their advertising or outreach.

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Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in RA: Retail Management, Analytics with Excel & Python..

Retail Management, Global Edition

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Provides a comprehensive overview of retail management principles, covering topics such as retail strategy, store management, merchandising, and customer service. It's a valuable resource for understanding the fundamentals of retail operations and strategic decision-making. It can be used as a textbook for the retail management portion of the course, providing a solid foundation for the analytics aspects.

Retail Management, Global Edition

Paperback

$$$

Python for Data Analysis

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Is an excellent resource for learning Pandas and other Python libraries used in data analysis. It provides in-depth explanations and practical examples. It is particularly useful for students who want to deepen their understanding of the Python tools used in the course. This book is commonly used as a reference by data scientists.

Python for Data Analysis

Paperback

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Python for Data Analysis

Kindle Edition

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