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Data Science Portfolio for Brian Beames, MBA, MT (ASCP)

Welcome to my Data Science Portfolio. I hope you enjoy the contents of this website and that it is successful in showcasing my skills in Data Science. I also hope that it can be of service to those interested in Data Science.

About Me

My interest in Data Science began after I learned about the job possibilities that I could possibly do after I earned my MBA. Since that time, I have been periodically learning about this subject and working on a few projects here and there on the side while I have been working full-time at my Medical Technologist job.

It is a desire of mine to obtain a work from home position. I do have experience working from home since this is how I earned my MBA.

Resume. This has my current contact information.
MBA College Transcript. Please notice that I did very well in the statistics course.

My data science profiles:

Kaggle profile
Github profile

Projects

Kaggle Competitions:

CareerCon 2019 - Help Navigate Robots
Completed: 2018
Ranking: 98% (Lowest is best)
This competition helped me to advance in the Kaggle ranking system.

Housing prices Competition for Kaggle Learn Users
Completed: Aug 2020
Ranking: 23%

OSIC pulmonary competition
What I learned from the OSIC pulmonary fibrosis competition
Completed: Sep 2020
Ranking: 18%

OpenVaccine competition (No submission)
Main objective and accomplishment: Transform a json file into a pandas dataframe which was then converted into CSV file. CSV file was then to be used for the program Orange.
See the comment section to the notebook above to see what I learned from this competition.
Completed: Sep/Oct 2020

Connect X competition
Completed as part of a course (Reinforcement Learning Course)
Completed: Nov 2020
Ranking: 91%

A small project:
I wrote code to help me to write code for this website.
Completed: October 28, 2020

Certifications

From Kaggle Courses:

Advanced SQL
Computer Vision
Data Cleaning
Data Visualization
Feature Engineering
Intermediate Machine Learning
Intro to Deep Learning
Intro to Game AI and Reinforcement Learning
Intro to SQL
Machine Learning Explainability
Microchallenges
Natural Language Processing
Pandas

Courses I audited without obtaining a certificate:

Kaggle Python Class
Edx Python Absolute Beginner class
Edx Python for Data Science
Edx Probability and Statistics Using Python
Edx Python Fundamentals

Certs Big Data and Hadoop:

Lesson 1 Introduction
Lesson 2 Hadoop Architecture
Lesson 3 Hadoop Deployment
Lesson 4 MapReduce
Lesson 5 Advanced HDFS and MapReduce

Certs Tableau:

Lesson 1 Feild Types and Visual Cues
Lesson 2 Data Connection in Tableau Interface
Lesson 3 Organizing and Simplifying Data
Lesson 4 Formatting and Annotations
Lesson 5 Special Field Types
Lesson 6 Generated Fields
Lesson 7 Chart Types
Lesson 8 Calculations
Lesson 9 Parameters
Lesson 10 Mapping
Lesson 11 Statistics
Lesson 12 Dashboards

Certs Excel:

Lesson 1
Lesson 2
Lesson 3
Lesson 4
Lesson 5
Lesson 6
Lesson 7

Skills

Microsoft Word, Excel, and Access. In fact one of my supervisors in my evaluation recognized my expertise in Access.
Basic webpage/website building (as is evidenced by this website)
Github repository for this website
Microsoft Expression Web
PyCharm
Notepad++
Mathematics
Data Visualization
AutoML Software:
Orange (which I learned in the OpenVaccine Kaggle competition).  This is an example of an Orange workflow created for the OpenVaccine Kaggle Competition.
RapidMiner

Statistics:
This is a statistics project I worked on for my MBA which dealt with this dataset. Here is some data visualization associated with that dataset created from this notebook:
distribution plot scatterplot

Miscellaneous Concepts I have learned

On November 11, 2020, I was motivated by this discussion in a Kaggle competition to learn from this article that Pytorch is very similar in concept to Tensorflow but uses different coding to essentially do the same thing.
I also learned from this article that I would like to start using JupyterLab rather than Jupyter Notebooks to do coding work. I really liked how you can do the dark theme with JupyterLab which required code to accomplish this in Jupyter Notebook.
I have also determined that when I write notebooks, I need to state the objective of what the notebook is trying to accomplish. I also need to state what each line of code is trying to do.

Resources

Please click here to see a comprehensive list bookmarks, books, github repositories, and data science articles I have at my disposal to assist me in doing data science.

This site was last updated on January 30, 2021

Copyright @ 2020 All Rights Reserved.

A special thank you to the website thesitewizard.com for the assistance in the creation of this website.

Another special thank you to Natassha Selvaraj for writing her article which inspired the writing of this webpage.