Thanks for taking a moment to visit, and see what I've been working on. This site is currently under construction, however the contact details should remain the same. Please reach out or revisit at a later time should you happen to have any questions, or need further details on something you see here.
This site serves as a portfolio of work so far, the steps I've taken to work on those projects, and a timeline of my efforts in Data Analysis and FrontEnd Web Development
I plan on adding in a blog that details learning and work starting in November.
The blog has been started! You can find the link in the navigation bar to the left on the desktop. If you happen to be on mobile, here's the link: Blog.
I originally began the Google Data Analytics Certificate in June 2021, after learning about it from a creator on TikTok. I found myself finishing the six month program within a month, while working full time. I learned a lot about how data is gathered, organized, and then analyzed for insights. I was really excited to jump into a new field and use the skills learned from the course in a new career.
However, I was not fully prepared for the job search to gain an entry level role in Data Analytics. I spent about two months getting more certificates and skills under my belt, but was unsure if I was ready for employment, considering I had not heard back from the applications that I had sent out. I then decided to take some time for learning FrontEnd Web Development as an alternate route into a career in Tech.
In October, I found that another creator on TikTok advertised for the Merit America program, which offered BootCamp like learning with payment only being required after getting employed at a certain salary range. I looked into the organization, found it offers not only intense learning and training, but strong career coaching, and that they were offering a program in Data Analysis. I signed up, excited to start right away, considering I had spent about a month on my other efforts in Web Development. It took some time for the response, since they had gotten a lot of inquiries from the TikTok advertisement, but I was accepted!
When I was accepted, I found I was in the January program instead. I missed the deadline for the pre-work to be done for the October class. Thankfully, they made an exception for my case once I reached out, and allowed me the opportunity to get the pre-work done before the October cohort began. I spent a day fully involved in the EdX course and completed the Data Science: R Basics material, earning a certificate from DataCamp on the course as well.
With that certification complete, as of October 18th, 2021, I am currently enrolled in the first cohort of the Data Analytics program offered by Merit America.
Here are the projects that I worked on since July 2021:
Following the previous project, I've joined in on the Onyx Data #datadna December Challenge, where participants were asked to analyze the Billboard Top 100 Christmas Carol Dataset, and try to answer which Christmas Song was the greatest.
To learn more about this challenge, please visit Onyx Data's website here:
OnyxData #Datadna December Challenge
To see the full viz please visit the following link:
Onyx December Challenge Viz
If you happen to check out the full Viz, do be sure to toggle over to the fire-side!
Recently, Dataxp.ai provided a project idea to work on, to display our analysis and visualization skills. This was not a guided project, but did include some foundations that we were to keep in mind:
Using the open source Airbnb dataset, build a dashboard to help property owners and investors understand the Airbnb property market. Describe the Airbnb property market by showing the number of properties with specific property attributes.
In this project I used Python and the following libraries: NumPy, Pandas, DataPrep, and NLTK, along with Tableau to answer the following questions:
How can we help property owners and investors get a high-level overview of the property market? What is the average rental price for apartments in your chosen city? What number of bedrooms is the most common? What proportion of Airbnb rentals have a swimming pool, air-conditioning, washing machine, etc?
The full dashboard can be viewed here:
Tableau Public Viz
Another project provided by the Coursera Tableau course, where the learners were guided to create a dashboard that includes filters and visuals based on which bourough was selected. Not super flashy, but nice and functional!
Tableau Viz Link
Going a bit further into Tableau, I had followed a guided project with Coursera that provided a general idea of how to get this started, and allowed the user to complete this on their own. Originally this was meant to be a Big Number KPI board,
However I did want to go a bit further than just numbers. As this was a project, I did take liberty with the colors as well. Based on the 2020 version of the Tableau Sample data set "SuperStore". It was pretty fun! :)
Tableau Viz Link
Looking a bit further into Tableau, I have taken an additional Coursera course into using the Tableau platform. One of the assignments tasks the learner with picking a project from the Makeover Monday program, and submitting an improved visualization.
To save on loading time, I've provided a screenshot above, but below you can visit the project directly. This was based on #MakeoverMonday 2021 Week 34, on an analysis of entry level positions requiring years of experience for qualification.
Tableau Viz link
Project with SMSS, SQL, and Power BI Using SQL Server Management Studio (SSMS), created a database from a cleaned excel dataset, created SQL query to bring data into PowerBI, and then created Dashboard visualization to answer the following business requirements:
Build a visual data story or dashboard using Power BI to present to the stakeholders answering these questions:
"Is our Hotel revenue growing by year?"
We have two hotel types, so it would be good to segment revenue by hotel type
"Should we increase our parking lot size?"
We want to understand if there is a trend in guests with personal cars
"What trends can we see in the data?"
Focus on average daily rate and guests to explore seasonality
This project will include the dataset, SQL, and PowerBI template, and a screenshot of the final dashboard.
Project provided by Absent Data: https://youtu.be/S2zBHmkRbhY
SMSS_PowerBI_Dashboard_Project on Github
The course ends with a choice between two data sets, and asks that the student conduct a Capstone project to provide an example of what was learned in the course. I chose the Bellabeat project, which offered a dataset that was provided from Kaggle, and asked me to analyze the data collected on a competitor smart device product.
I used Rstudio to analyze the fitbit data that was provided. In this project I found that the usage data was rather detailed, but did not entirely match what Bellabeat was offering, so I had kept the analysis high level and general to be able to compare the two.
Through the analysis of the data, I was able to learn that the fitbit users who were the most active were also reporting longer sleep as a correlation. My final suggestion was that this could be used by the Bellabeat team to inform their target audience on how to reduce stress through more exercise, as it may lead to longer sleep, which could enhance their product offerings.
Here is the R analysis for the Capstone Project:
R Analysis for BellaBeat Capstone Project
Here you can find the slides presentation I created for the project:
Bellabeat Presentation
And finally, here are the notes that I had used through the project to keep me on task:
Bellabeat Capstone Project Notes
Kaggle held a 30 days of Machine Learning event, where I was able to proceed through their courses to learn more about Python and beginner to intermediate Machine Learning.
I completed the courses, but did not participate in the final project. I did, however, use the python experience along with the documenation for the Seaborn and Matplotlib libraries to do an exploritory analysis of a sales data set that was available on Kaggle.
The analysis can be found here:
Sales Data Analysis using Python
The coding examples that were completed through the Python and Machine Learning Courses through Kaggle can also be found under my Kaggle Code page:
Tgill1085 Kaggle Code Page
Following my experience with the Sales Data Analysis, I felt that It may be good to check out any other known resources regarding Data Analysis and Python.
Having used FreeCodeCamp previously in learning about FrontEnd Web Development, I revisited the site and found they are offering a course in what I was looking for.
While taking the course with FreeCodeCamp, the material requires that python coding exercises be submitted for record keeping and grading. They suggest REPLit for ease of use in this case, as it does not require any downloads, and can be easily shared. I had written the code for these Python exercises in my REPLit, but have also copied it over to my
Github account for keeping my code in one spot.
Here is my REPLit page, with the Python exercises and code that were submitted to FreeCodeCamp for my Data Analysis with Python Certificate:
Tasha Gill's REPLit
HackerRank is a website much like LeetCode, that provides both instruction and confirmation of coding ability. So far, I've certified on the site that I have basic Python and SQL knowledge, and as of October 18th, have three stars under Python, and two stars under SQL.
Here's my HackerRank profile link:
Tasha Gill's Hacker Rank Profile
Before I entered into the Merit America Program, I concluded that it may take much longer than a few months to break into the Data Analysis role that I wanted to prepare for.
Due to this, I decided to turn my efforts towards Front End Web Development.
I continued using the FreeCodeCamp site for the other courses in "Responsive Web Design", and "Javascript data structures and algorithms", as well as Colt Steele's Web Developer BootCamp on Udemy to do so.
These courses are still in progress, but will be on the back burner until I complete the Merit America Program. For now, this page will serve as part of what skills were learned in those courses.
This was the first Game Jam I've participated in. This particular game jam challenges developers to create and complete a game within 3 days while following a theme that was voted on by the community. This started on October 1st, and ended on October 4th, and the theme for the jam was "Unstable".
My partner, who introduced me to the Ludum Dare game jam, has a passion for programming and game design that has continued for decades. He participates in these jams to enhance his skills and have fun with development.
Thankfully I was able to participate with him on this one, providing the menus and most of the pixel art. We completed the game barely on-time, and while we did not place very high, we did enjoy the process and the community effort along the way.
Electro-Twixt: Our Ludum Dare 49 Game Submission
For any further questions, please send me an email, or message me on LinkedIn, thanks!