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Alex Mannella

In this Capstone Project, you'll bring together all the new skills and insights you've learned through the four courses. You'll be given a 'mock' client problem and a data set. You'll need to analyze the data to gain business insights, research the client's domain area, and create recommendations. You'll then need to visualize the data in a client-facing presentation. You'll bring it all together in a recorded video presentation.

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In this Capstone Project, you'll bring together all the new skills and insights you've learned through the four courses. You'll be given a 'mock' client problem and a data set. You'll need to analyze the data to gain business insights, research the client's domain area, and create recommendations. You'll then need to visualize the data in a client-facing presentation. You'll bring it all together in a recorded video presentation.

This course was created by PricewaterhouseCoopers LLP with an address at 300 Madison Avenue, New York, New York, 10017.

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Syllabus

Understanding the Business Problem
In this course, you will be using the skills you’ve been developing throughout the series of PwC courses to create and present a deliverable for a client.You’re going to determine your approach for analysis, use the information provided by the client to conduct an analysis, determine the best way to show your findings and then develop a plan to deliver your results and recommendations to the client in a video presentation.In this course, you will be acting as a consultant interacting with a client, Electric Growers. The client needs your strong data analytics and Excel skills to analyze data and help them make smart decisions to enable the company’s move into the security devices and services market. Each week, the client, represented by Michele Tran, a Vice President of Operations from Electric Growers, and the management team, will ask you to use and analyze the data, provided by the client, to answer a series of questions that will help them make decisions.You’ll receive peer feedback that you can use to enhance future presentations. This course was created by PricewaterhouseCoopers LLP with an address at 300 Madison Avenue, New York, New York, 10017.
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Analyzing the Business Problem
This week, you will be using the results of last week’s analysis to come up with some hypotheses. You will be answering questions such as: Who are the ideal customers that should be targeted? How should they be approached to maximize the sales of the client’s new home security systems? Using the data, figure out the attributes of the customer who wants to install an advanced, hi-tech security system and the attributes of a person who would switch security system providers. Continue to use the knowledge you’ve acquired in the other courses that you’ve taken in this series.
Creating a visual representation of your analysis results
This week, the client has more questions for you to answer to further develop the profile of potential customers. This includes finding which cities to target and how to evaluate them. You will have access to crime rates, population, housing growth city wide data and segmentation distribution dumps to help in your analysis.
Building a presentation for the client meeting
This week, you will be taking your findings and detailed analysis on plans to launch the new home security system and put them into a PowerPoint presentation deck for Michele Tran and the management team. The presentation should be about 10 slides and should follow the guidelines and best practices of presenting to a client that were covered in the earlier courses within this specialization. Ms. Tran wants to review it and give you feedback, if needed, before having it presented to the management team.This is a chance to use what you learned about creating a presentation, using PowerPoint tools, creating charts and other methods of enhancing a presentation.
Presenting your results to the client
This week, Ms. Tran has reviewed your draft presentation so it is now time to refine and make changes or additions to enhance the presentation before presenting it to the management team via video. Once you’ve finalized your presentation, you will present it in a video using your smartphone or computer. When you’re satisfied with the PowerPoint presentation and video, you will be submitting both for peer review. You can use this feedback for current and future presentations that you will make during your career.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Covers in-demand data skills utilized in industry
Demonstrates relevant concepts in data visualization
Develops specialized data analytics proficiency
Provides hands-on practice through a mock client project
Offered by PricewaterhouseCoopers LLP, renowned for its expertise in data analytics
Requires prior knowledge in data analysis, limiting accessibility for beginners

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Reviews summary

Pwc final project course

According to students, The PwC Final Project was a relatively positive course with an engaging Final project and Case Study.

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 Data Analysis and Presentation Skills: the PwC Approach Final Project with these activities:
Read 'Data Analysis with Python'
Gain a strong foundation in data analysis using Python by reading this comprehensive book.
Show steps
  • Start by reading the introductory chapters to get an overview of data analysis with Python
  • Focus on chapters covering data manipulation, cleaning, and exploration
  • Read chapters on data visualization and communication
Learn basic statistics
Start by reviewing basic statistical concepts to ensure you have a solid foundation for the course material.
Browse courses on Statistical Concepts
Show steps
  • Review basic probability distributions
  • Practice calculating measures of central tendency
  • Brush up on hypothesis testing
Follow data analysis tutorials
Enhance your understanding of data analysis techniques by following guided tutorials.
Browse courses on Data Analysis Techniques
Show steps
  • Find tutorials on data cleaning and preparation
  • Complete tutorials on data visualization
  • Work through tutorials on predictive modeling
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend data analysis workshops
Enhance your data analysis skills by attending workshops led by industry experts.
Browse courses on Skill Development
Show steps
  • Research and identify relevant data analysis workshops
  • Register for workshops that align with your interests and learning goals
  • Actively participate in the workshops and take notes
  • Practice the techniques and concepts learned in the workshops
Attend data analysis meetups
Expand your network and learn from others in the field by attending data analysis meetups.
Browse courses on Networking
Show steps
  • Find local data analysis meetups
  • Attend meetups and introduce yourself to others
  • Engage in discussions and ask questions
  • Follow up with people you meet
Solve data analysis practice problems
Sharpen your data analysis skills by solving practice problems.
Show steps
  • Find practice problems on data cleaning and preparation
  • Solve problems on data visualization
  • Attempt problems on predictive modeling
Contribute to open-source data analysis projects
Gain hands-on experience and contribute to the data analysis community by working on open-source projects.
Browse courses on Open Source
Show steps
  • Find open-source data analysis projects on platforms like GitHub
  • Review the project documentation and identify areas where you can contribute
  • Submit a pull request with your contributions
  • Respond to feedback and iterate on your contributions
Develop a data analysis project
Apply your data analysis skills to a real-world problem by developing a project.
Browse courses on Capstone Project
Show steps
  • Identify a business problem that requires data analysis
  • Collect and clean the necessary data
  • Analyze the data and draw insights
  • Communicate your findings through visualizations and reports

Career center

Learners who complete Data Analysis and Presentation Skills: the PwC Approach Final Project will develop knowledge and skills that may be useful to these careers:
Analyst
As a data analyst, a good portion of your efforts are spent on gathering, cleaning, and presenting data — much like what you will do in the Data Analysis and Presentation Skills: the PwC Approach Final Project. Using this data and your critical thinking skills, you will look for insights and patterns that help businesses make strategic decisions and solve problems. By enrolling in this course, you can refine your data analysis and presentation skills, giving you a competitive edge in this exciting career.
Business Analyst
Business analysts are in high demand due to their key role in bridging the gap between business and IT. You will work with stakeholders to understand their needs and then use your analytical skills to develop solutions that meet those needs. Furthermore, you will need to clearly communicate your findings and recommendations to both technical and non-technical audiences. As you will refine both your data analysis and presentation skills from taking this course, you will be well on your way to a successful career as a business analyst.
Consultant
Consultants provide expert advice to businesses on a wide range of topics, including data analysis and presentation. In this role, you will use your skills to help clients solve problems, make better decisions, and improve their overall performance. The Data Analysis and Presentation Skills: the PwC Approach Final Project course will help you build the skills you need to be a successful consultant, including data analysis, problem-solving, and communication skills.
Data Mining Analyst
Data mining analysts are responsible for extracting valuable information from large datasets. This information can be used to improve business processes, identify new opportunities, and make better decisions. If you are interested in a career as a data mining analyst, taking the Data Analysis and Presentation Skills: the PwC Approach Final Project can help you build the skills you need to be successful.
Data Scientist
Data scientists use their skills in mathematics, statistics, and computer science to solve business problems. They are in high demand due to the increasing amount of data that businesses are collecting. By taking the Data Analysis and Presentation Skills: the PwC Approach Final Project, you can gain the skills you need to become a successful data scientist.
Financial Analyst
Financial analysts use their skills in data analysis to make investment recommendations and provide financial advice to clients. They may work for investment banks, hedge funds, or other financial institutions. The Data Analysis and Presentation Skills: the PwC Approach Final Project can help you build the skills you need to be successful in this role.
Market Research Analyst
Market research analysts collect and analyze data about consumer behavior, market trends, and other factors that can affect a business's success. They use this information to help businesses make better decisions about their products, services, and marketing strategies. The Data Analysis and Presentation Skills: the PwC Approach Final Project can help you build the skills you need to be successful in this role.
Operations Research Analyst
Operations research analysts use their skills in mathematics, statistics, and computer science to solve business problems. They may work in a variety of industries, including manufacturing, transportation, and healthcare. The Data Analysis and Presentation Skills: the PwC Approach Final Project can help you build the skills you need to be successful in this role.
Product Manager
Product managers are responsible for the development and launch of new products and services. They work with cross-functional teams to ensure that products meet customer needs and are commercially successful. The Data Analysis and Presentation Skills: the PwC Approach Final Project can help you build the skills you need to be successful in this role, such as data analysis, problem-solving, and communication skills.
Project Manager
Project managers are responsible for planning and executing projects of all sizes. They work with stakeholders to define project scope, develop budgets, and manage timelines. The Data Analysis and Presentation Skills: the PwC Approach Final Project can help you build the skills you need to be successful in this role, such as data analysis, problem-solving, and communication skills.
Quantitative Analyst
Quantitative analysts use their skills in mathematics, statistics, and computer science to develop and implement financial models. They may work for investment banks, hedge funds, or other financial institutions. The Data Analysis and Presentation Skills: the PwC Approach Final Project can help you build the skills you need to be successful in this role.
Risk Analyst
Risk analysts identify and assess risks that could affect a business. They develop and implement strategies to mitigate these risks. The Data Analysis and Presentation Skills: the PwC Approach Final Project can help you build the skills you need to be successful in this role, such as data analysis, problem-solving, and communication skills.
Software Engineer
Software engineers design, develop, and test software applications. They may work in a variety of industries, including technology, healthcare, and finance. The Data Analysis and Presentation Skills: the PwC Approach Final Project can help you build the skills you need to be successful in this role, such as data analysis, problem-solving, and communication skills.
Statistician
Statisticians collect, analyze, and interpret data. They use their skills to solve problems and make informed decisions. The Data Analysis and Presentation Skills: the PwC Approach Final Project can help you build the skills you need to be successful in this role, such as data analysis, problem-solving, and communication skills.
Teacher
Teachers at all levels and subjects use effective presentation skills to convey lesson content to students, but data analysis in education is an emerging field that is vital to continued institutional improvement. From a school's test score results to student performance, teachers can leverage data analysis to identify areas of difficulty for both individual students and groups.

Reading list

We've selected 30 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 Data Analysis and Presentation Skills: the PwC Approach Final Project.
Provides a comprehensive overview of natural language processing concepts and techniques. It valuable resource for students and professionals who want to learn more about natural language processing.
Provides a comprehensive overview of causal inference, covering everything from the basics to more advanced topics like structural equation modeling and counterfactuals.
Provides a comprehensive overview of Bayesian data analysis, covering everything from the basics to more advanced topics like hierarchical models and Markov chain Monte Carlo.
Provides a comprehensive overview of data science concepts and techniques. It valuable resource for students and professionals who want to learn more about data science.
Provides a comprehensive overview of computer vision concepts and techniques. It valuable resource for students and professionals who want to learn more about computer vision.
Provides a comprehensive overview of data mining concepts and techniques. It valuable resource for students and professionals who want to learn more about data mining.
Provides a comprehensive overview of machine learning algorithms. It valuable resource for students and professionals who want to learn more about machine learning.
Provides a comprehensive overview of deep learning concepts and techniques. It valuable resource for students and professionals who want to learn more about deep learning.
Offers a practical guide to data visualization, covering a wide range of techniques and best practices. It is an excellent resource for anyone who wants to learn how to create effective and informative visualizations.
Covers the fundamentals of data analysis using Python, including data cleaning, manipulation, exploration, and visualization. Provides hands-on examples and exercises to help learners develop their data analysis skills.
Provides a practical introduction to data analysis using Power BI, including techniques for data cleaning, data analysis, and data visualization. It valuable resource for students and professionals who want to learn more about data analysis using Power BI.
Provides a comprehensive introduction to Python for data analysis. It covers everything from the basics of Python to more advanced topics like data manipulation and visualization.
Provides a practical introduction to data analysis using Excel, including techniques for data cleaning, data analysis, and data visualization. It valuable resource for students and professionals who want to learn more about data analysis using Excel.
Explores the transformative potential of data in business. Provides case studies and examples of how data analytics can be used to drive innovation, growth, and profitability.
Provides practical advice on how to present data in a compelling and engaging way. Covers topics such as data visualization, storytelling techniques, and audience engagement.
Introduces the basics of statistics in a clear and accessible way. Provides real-world examples and exercises to help learners understand the principles of data analysis and interpretation.
Provides a practical introduction to data analysis using R, including techniques for data cleaning, data analysis, and data visualization. It valuable resource for students and professionals who want to learn more about data analysis using R.
Provides a practical introduction to data analysis using Python, including techniques for data cleaning, data analysis, and data visualization. It valuable resource for students and professionals who want to learn more about data analysis using Python.
Provides a business-oriented introduction to data science. It covers everything from the basics of data mining to more advanced topics like machine learning and predictive analytics.
Provides a practical introduction to data mining, with a focus on machine learning algorithms. It covers everything from data preparation to model evaluation.
Provides a comprehensive guide to using Excel for data analysis. It covers a wide range of topics, from data cleaning to data visualization, making it a valuable resource for anyone who wants to learn how to use Excel effectively for data analysis.
A comprehensive guide to using Microsoft Excel, covering basic and advanced features such as data entry, formulas, functions, and charting. Provides step-by-step instructions and real-world examples to help learners master Excel.
Provides step-by-step instructions on how to use Excel 2016. It covers everything from basic tasks like creating and formatting spreadsheets to more advanced tasks like using formulas and functions.
Examines the ethical and societal implications of data collection and analysis. Raises important questions about privacy, surveillance, and the responsible use of data.
Provides a comprehensive overview of dashboards, covering everything from design principles to implementation best practices. It great resource for anyone who wants to learn more about how to create effective dashboards.
Provides a comprehensive overview of statistical methods for data analysis, including descriptive statistics, inferential statistics, and regression analysis. It valuable resource for students and professionals who want to learn more about statistical methods.

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