reading-notes

Code Fellows Reading Notes

Code 102 Reading Notes

• Class 1 - Learning Markdown
• Class 2 - The Coder’s Computer
• Class 3 - Revisions and the Cloud
• Class 4 - Structure Web Pages with HTML
• Class 5 - Design Web Pages with CSS
• Class 6 - Activate Web Pages with JavaScript
• Class 7 - Programming with JavaScript
• Class 8 - Operators and Loops

---

Code 201 Reading Notes

• Class 1 - HTML, CSS, & JavaScript Background
• Class 2 - HTML, CSS, & JavaScript Review
• Class 3 - HTML Lists, Control Flow with JS, and the CSS Box Model
• Class 4 - HTML Links, JS Functions, and Intro to CSS Layout
• Class 5 - Images, Color, Text
• Class 6 - Problem Domain, Objects, and the DOM
• Class 7 - Object-Oriented Programming, HTML Tables
• Class 8 - CSS Layout
• Class 9 - Forms and JS Events
• Class 10 - Debugging
• Class 11 - Audio, Video, Images
• Class 12 - Canvas and Chart.js
• Class 13 - Local Storage
• Class 14 - Transforms, Transitions, & Animations
• Class 15 - Psychological Safety
• Psychological Safety

---

Code 301 Reading Notes

• Class 1 - Introduction to React and Components
• Class 2 - State and Props
• Class 3 - Passing Functions as Props
• Class 4 - React and Forms
• Class 5 - Putting It All Together
• Class 6 - NODE.JS
• Class 7 - REST
• Class 8 - APIs
• Class 9 - Functional Programming
• Class 10 - In Memory Storage
• Class 11 - MongoDB and Mongoose
• Class 12 - CRUD
• Class 13 - More CRUD
• Class 14 - Diversity & Inclusion in the Tech Industry
• Class 15 - Authentication

---

Code 401 Reading Notes

• SQL Practice
• Command Line Practice
• Growth Mindset
• Data Structure and Algorithms
• Engineering Readings
• Class 1 - Pain & Suffering and Big O Notation
• Class 2 - Testing and Modules
• Class 3 - FileIO & Exceptions
• Class 4 - Classes & Objects, Thinking Recursively, and Pytest Fixtures & Coverage
• Class 5 - Linked Lists
• Class 6 -
• Class 7 - Python Scope
• Class 8 - List Comprehensions
• Class 9 -
• Class 10 - Stacks and Queues
• Class 11 - Data Analysis
• Class 12 - Pandas
• Class 13 - Linear Regression in Python
• Class 14 - Data Visualization
• Class 15 - Trees
• Class 16 - Serverless Functions
• Class 17 - Web Scraping
• Class 18 - Encryption, Decryption & Hacking
• Class 19 - Regular Expressions & shutil
• Class 26 - Django
• Class 27 - Django Models
• Class 28 - Django Forms
• Class 29 - Django Custom User
• Class 30 - Hash Tables
• Class 31 - Django REST Framework & Docker
• Class 32 - Django Permissions
• Class 33 - Authentication & Production Server
• Class 34 - API Deployment
• Class 35 - Graphs
• Class 36 - DSA Review
• Class 39 - React Context

Microsoft Data Scientist Certification

• Module 1 - Create machine learning models
  • Module 1-1 Explore and analyze data with Python
  • Module 1-2 Train and evaluate regression models
  • Module 1-3 Train and evaluate classification models
  • Module 1-4 Train and evaluate clustering models
  • Module 1-5 Train and evaluate deep learning models
• Module 2 - Microsoft Azure AI Fundamentals: Explore visual tools for machine learning
  • Module 2-1 Use Automated Machine Learning in Azure Machine Learning
  • Module 2-2 Create a regression model with Azure Machine Learning designer
  • Module 2-3 Create a classification model with Azure Machine Learning designer
  • Module 2-4 Create a clustering model with Azure Machine Learning designer
• Module 3 - Build and operate machine learning solutions with Azure Machine Learning
  • Module 3-1 Introduction to the Azure Machine Learning SDK
  • Module 3-2 Train a machine learning model with Azure Machine Learning
  • Module 3-3 Work with Data in Azure Machine Learning
  • Module 3-4 Work with Compute in Azure Machine Learning
  • Module 3-5 Orchestrate machine learning with pipelines
  • Module 3-6 Deploy real-time machine learning services with Azure Machine Learning
  • Module 3-7 Deploy batch inference pipelines with Azure Machine Learning
  • Module 3-8 Tune hyper parameters with Azure Machine Learning
  • Module 3-9 Automate machine learning model selection with Azure Machine Learning
  • Module 3-10 Explore differential privacy
  • Module 3-11 Explain machine learning models with Azure Machine Learning
  • Module 3-12 Detect and mitigate unfairness in models with Azure Machine Learning
  • Module 3-13 Monitor models with Azure Machine Learning
  • Module 3-14 Monitor data drift with Azure Machine Learning
  • Module 3-15 Explore security concepts in Azure Machine Learning

Machine Learning Notes (Stanford Lecture)

• Linear Regression, Gradient Descent, Batch Gradient Descent, and Stochastic Gradient Descent
• Locally Weighted Regression, Probabilistic Interpretation, Logistic Regression, and Newton’s Method

Data Science for Business

• Chapter 1 - Data Mining and Data-Analytic Thinking
• Chapter 2 - Business Problems and Data Science Solutions
• Chapter 3 - Introduction to Predictive Modeling: From Correlation to Supervised Segmentation
• Chapter 4 - Fitting a Model to Data
• Chapter 5 - Overfitting and Its Avoidance
• Chapter 6 - Similarity, Neighbors, and Clusters
• Chapter 7 - Data Exploration - A Key Step in the Data Science Process
• Chapter 8 - Similarity, Neighbors, and Clusters

Practical Statistics for Data Scientists

• Chapter 1 - Exploratory Data Analysis
• Chapter 2 - Data and Sampling Distributions
• Chapter 3 - Statistical Experiments and Significance Testing
• Chapter 4 - Regression and Prediction
• Chapter 5 -
• Chapter 6 -
• Chapter 7 -

CompTIA Data+ Exam Prep

• Objective 1 - Data Concepts and Environments

---

About Me

My name is Jason Christopher and I live in Oklahoma City with my wife and 2 sons. We’ve been stationed in OKC since 2013 and will be here for the foreseeable future since my wife is on active duty orders with the Oklahoma Army National Guard. I was active duty Air Force for 8 years before deciding I’ve had enough and transitioned to the Air Force Reserves where I still do the same job of being an Air Battle Manager on the E-3 AWACS…but now only part-time and without the extra “stuff” from active duty! I have a passion for software development and data science and have a desire to never stop learning!

GitHub Profile link: https://github.com/jason-christopher