Data Analytics Portfolio Project

Join our intensive one-month program to learn how to create an advanced application from scratch! Our professional Data Analysts/Scientists will guide you through a project-based learning experience, helping you build an impressive portfolio piece to showcase your software development skills.
Your Instructor
Alfonso Alvarez
is a senior data science consultant on data-driven innovation, and a researcher on the intersection between environmental economics and public health outcomes. He holds a Ph.D. in Public Policy and a Master in Statistics from the University of Texas at Austin, and a Master of Public Policy with a focus on Applied Econometrics from the University of California, Berkeley.
Course Overview

Join our intensive one-month program to learn how to create an advanced application from scratch! Our professional Data Analysts/Scientists will guide you through a project-based learning experience, helping you build an impressive portfolio piece to showcase your software development skills.

What you’ll learn

Course Objectives

  • Provide students with an in-depth understanding of Data Analytics  
  • Offer a project-based learning environment, facilitating the practical application of theoretical knowledge in a real-world context.
  • Enable students to complete an advanced application project suitable for display in their professional portfolios.
  • Facilitate students' learning under the mentorship of an experienced Data Analyst, ensuring guidance and support throughout the course.

Course Prerequisites

  • Completion of a course in Intro to Data Analytics or Advanced Data Analytics will provide a fundamental understanding of the project.
  • Prior knowledge and skills in Data Analytics or Data Science, specifically in certain areas.
  • College and university students studying Data Science or Data Analytics who are interested in a portfolio project.
  • Proficiency in Python, Power BI, SQL, and Machine Learning

What does this course look like?

Who is it for?

Course Syllabus

Course Program Stages
4 weeks (20 hours per week)
Total Hours:
80 hours
5 Hours
Project Planning

The first stage is all about “What do we want?” Project planning is a vital role in the analytics delivery lifecycle since this is the part where the team estimates the cost and defines the requirements of the project. This stage answer key questions from the student:

  1. What data set and source will they be using? If the data set is public, then the student should provide a link to the data set. If the data set is not public, then the student should provide a summary of the observations, variables and format they have them available.
  1. What is the core question the analysis will seek to answer?
  1. How will we measure the results once they are presented?

5 Hours
Gathering Requirements & Analysis

The second step is gathering maximum information from the client requirements for the project. Discuss each detail and specification of the project with the customer. The team will then analyse the requirements keeping the design and architecture in mind. The main goal of this stage is that everyone understands even the minute detail of the requirement. Databases, datasets, integration requirements, platform, dimensions, key metrics are to name the few requirements. The key questions to be answered in this stage will be:

  1. What software requirements does the student have?
  1. Is there any integration between the data set and the software that needs to be well defined?
  1. Are there specific timelines or deadlines that need to be met within the logic of the project?
  1. What Data or DevOps platform will be used to share updates about the project?
  1. What language or tool will be used to generate the data product?
  1. Are there any risks involved in the the deployment of the products or the analysis?
  1. How can we mitigate those risks?

10 Hours

In the design phase, the team scrutinizes whether the prepared design fulfils all the requirements of the end-user. Additionally, if the project is feasible for the customer technologically, practically, and financially. The key questions to be answered in this stage will be:

  1. Has the student met with the client to determine their needs?
  1. How will success be defined in the context of this project?
  1. Do we have any budget constraints that need to be taken into consideration for the project?
  1. Are there are workload/implementation risks we can envision?
  1. How can we mitigate the workload/implementation risks?  
50 Hours

Time to code! It means translating the design into databases, data lakes, and datasets. In this last stage, the tasks are divided into modules or units and assigned to various team members. Each team member will then start building the system by creating the databases, aggregating and cleaning the data, creating the analysis tools, reports, and dashboards.

This process will have several stages:

  1. Set up and access to all the sources
  1. Initial cleaning and integration of the data
  1. Development of descriptive and summary statistics for the product/model
  1. Development of an initial draft of the data product
  1. Validation with client of the requirements and structure of the data product
  1. Adjustment of data product based on feedback from client
10 Hours

Once the developers finish the build, then it is deployed in the testing environment. Then the testing team tests the functionality of the entire system. In this final phase, the testing is done to ensure that the entire application works according to the customer requirements  

The key stages for this section are the following:

  1. Pilot testing of the data product
  1. Deployment of the data product
  1. Validation from client and feedback
  1. Evaluation of the student and the data project

View the full program syllabus, click for access!

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Frequently asked questions
Do I need programming experience for your courses?

No, a basic level of computer literacy and a motivation to learn is all you need for most of our courses.

Who should take your courses?

The course is designed for diverse backgrounds; If programming or tech is a career track you really want to pursue, you can sign-up for our courses whether you are software engineer, product/program manager, analyst, researcher, consultant, student etc.

How much time do I need to spend studying outside of the classroom?

It can vary depending on your unique background. However, it usually takes 1-15 hours/week outside of the classroom for homework and study time.

Will I be given a certificate after the completion of the course?

Yes, you will be given a certificate of completion for this course after you pass your final exam.

Do you accept GI Bill®?

Yes, please refer to our Veterans page for more details.

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