My 10-Week Summer Plan: Building Toward the Career Fair

This post is a short update on my summer focus: preparing for the fall STEM career fair, strengthening my portfolio, and turning my current learning plan into clearer evidence of my data science skills.

In this post:

- End Goal: Career Fair
- The 10-Week Plan
- Updated Portfolio Deliverables
- Vacation and Reset

End Goal: Career Fair

On Friday, September 18, my university is hosting its fall STEM career fair. I graduated recently, but I have attended this career fair for the past two years and have found it very useful. A wide range of Michigan companies usually attend, and I am looking forward to making new connections, following up with familiar employers, and having stronger conversations about my work.

Front: Ray of Data Business Card

Back: Contact Info with QR code to LinkedIn

This year, I also have new business cards to share. My goal is to make it easier for recruiters and hiring managers to remember me and quickly find my portfolio, GitHub, blog, and project work.
One company I am especially interested in is an insurance company I interviewed with twice shortly after graduation. I still feel that it could be a strong fit for my skills and interests, but the interview process helped me see where my portfolio needed to be stronger. I had projects, but I do not think they showed the full range of skills I wanted to communicate clearly enough.

That is the main reason I created a 10-week summer plan. My goal is not just to add more work to my portfolio. My goal is to update my resume projects so they better reflect the roles I am applying for and the skills I want to use professionally.

The 10-Week Plan

For this portfolio sprint, I created four focused learning paths: dashboards, SQL, advanced analytics, and a capstone-style project. Each path is organized across weeks 0-11 with readings, YouTube support, Udemy course practice, weekly topic focuses, and minimum deliverables.

Week 0 is for setup. This includes gathering books and resources, checking my coding environments, organizing project folders, and reviewing topics I have already covered. Week 11 is for polishing my resume, GitHub, portfolio links, and elevator pitch before the career fair.

The four main learning paths are:

Course 1: Hospital Readmissions Predictive Modeling Capstone
This will be my main Python project. I plan to use Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurelien Geron to support the machine learning workflow, including classification, preprocessing, model evaluation, ensembles, and reproducible project structure.

Course 2: SQL for Data Science and Business Analytics
This path will focus on strengthening SQL through business-style questions and practical database work. I plan to use SQL for Data Analysis by Cathy Tanimura to review topics such as CTEs, window functions, data transformation, and analytics-focused queries.

Course 3: Advanced Predictive Modeling and CNN Practice
This path will focus on a small deep learning proof of concept, likely connected to counting trees from aerial images. I plan to use Deep Learning with Python by Francois Chollet to support the CNN and computer vision side of the project.

Course 4: Dashboard and Stakeholder Communication
This path will focus on creating a smaller business-style dashboard and improving how I communicate insights visually. I plan to use Storytelling with Data by Cole Nussbaumer Knaflic to keep the dashboard focused, clear, and audience-aware.

I also plan to use targeted YouTube resources when I need extra support. StatQuest will help with machine learning and model evaluation, Alex The Analyst will support SQL review, DeepLearning.AI will support neural network and CNN concepts, and Guy in a Cube will help with Power BI report design and publishing.

The point of this plan is not to finish every possible topic. The point is to stay focused, build consistently, and turn my learning into visible portfolio work.

Updated Portfolio Deliverables

Each learning path will have something I can add to GitHub, my resume, or my professional portfolio. Each week also has a minimum viable deliverable, so I can keep making progress toward the larger projects without getting stuck waiting for everything to be perfect.

Course 1: Hospital Readmissions Predictive Modeling Capstone
I liked the structure of my COVID-19 capstone in R, and I want to work through the full data science workflow again in Python. This project will include a research question, cleaning, exploratory data analysis, machine learning, evaluation, a video presentation, and a final report. I already have a question started, some research completed, and a dataset I began cleaning. This will be my highest-priority project.

Course 2: SQL for Data Science and Business Analytics
This path may not have one large final project, but it will have a GitHub repository showing the SQL practice I completed over the summer. SQL is a core skill for data analyst, business intelligence, data science, and related technical roles, and I want to become much more confident with it. This path will help me review fundamentals while also exploring more advanced techniques that were not covered deeply in my previous coursework.

Course 3: Advanced Predictive Modeling and CNN Practice
This will likely be the most difficult project, but it is also one of the projects I am most interested in building. I have built a few simple computer vision convolutional neural networks before through a hackathon and class labs, but this time I want to find my own dataset, prepare the data, and complete a proof of concept CNN for counting trees in aerial photos. This project would help me show interest in more advanced machine learning work and connect to the kind of applied modeling problems I learned about during the insurance interview process.

Course 4: Dashboard and Stakeholder Communication
My first data science interview was with a manufacturing company, and they were very interested in Power BI. The insurance predictive modeler role I interviewed for did not focus on Power BI as much, but the related BI developer role did. Because of that, I want to build a stronger business-focused dashboard project, likely related to manufacturing, to add alongside or eventually replace my Great British Bake Off dashboard on my resume. My goal is to complete my Power BI course first, then apply what I learn in a simpler strong 2-3 page dashboard.

Together, these projects are meant to show that I am ready for a junior role, willing to keep learning, and capable of turning feedback into stronger portfolio work.

Vacation and Reset

Since this week is technically Week -1 before my 10-week sprint begins, I am using it as a chance to reset. I split the week into two mini vacations: one with my husband and one with my mom.
From Monday to Wednesday, my husband and I went to Mackinac Island and enjoyed a wonderful 8.2-mile tandem bike ride around the island. The views were beautiful, the weather was just about perfect, and it was exactly the kind of break I needed before starting a focused summer of portfolio work.

 

Mackinac Bridge from sunset cruise

Love this shot with the symmetry under the bridge

Took some time to slow down on Mackinac Island

I loved the trip so much that I am taking my mom back this weekend. She even agreed to go parasailing with me, which I am very excited about.

This week has been a good reminder that rest is part of building momentum too. I am still focused on my career goals, but I also want this summer plan to be sustainable. After some time near the water, with family, photos, and a little adventure, I feel ready to come back recharged and begin the next phase of building my portfolio.