Christopher Loc Le

I was born in a small city called Tuy Hoa, Vietnam where I found interests in engineering from my dad’s garage.

I took 2 gap years to study Full-stack development and Machine Learning at CoderSchool. During this time, I learned iOS development and found a project named Mind Your Neck. The project stopped as I thought I still need to learn a lot to scale in production.

I started college at Augustana College where I earned Donald E. McLaughlin Award for Excellence and Achievement in Computer Science (top 1% of class). During this 4 years, I had a chance to intern at both startups IMI.AI, CloudQuant, and big tech such as Google - Cloud team. I also had experience in Machine Learning while working Dr. Tauheed. At the end of these 4 year, I am confident to create and scale a full-stack web app from sratch with data analytics. My current knowledge contains Full-stack Development, AI, Networking/Infrastructure, and System Engineering.

While working in industry, I found many software optimization still relies on hardware configuration in which I have not studied at college. I am studying hardware while working with CYOBot to bring robotics and programming learning to everyone. My experience is very diversified but I am a quick learner and goal-oriented. I’m on my quest to find what my specialization is.

My goal is that one day to connect all of these dots needed for a strong system together. I hope to share my knowledge with others by my experience with DevRel.

I read a lot about philosophy, religion, and economics. I also taking photos at Unsplash

I’m best reached via email. I’m always open to interesting conversations and collaboration.

Awards:

2nd Place Developer Week Hackathon 2019.
1st place in AngelHack + AWS Hackathon 2019.
1st Place Midwest Region (MW) of the Consortium for Computing Sciences in Colleges (CCSC).

Certifications: Tensorflow Developer (Google), Machine Learning System Design (Educative), Tableau and R, PowerBi, R for Excel users, SQL.
Related course-works: Operating System, Machine Learning, Software Development, Data Structures and Algorithms, Cybersecurity and Networking, Database management.
Extracurricular: Founder - Google Developer Student Club, Mentor - HackMIT, Software Engineer - ACES App, Grader - Augustana College’s SQL Class.

news

Jan 24, 2024	While Go, Rust, and JS are more popular or performance-wise for web servers, if I have to use Python only (since it is also popular for data science), here are what I am using already for almost any needs: General - Build a general website: Web development: Django (+ HTML, CSS). Backend: SQL + sqlite3, or NoSQL (ex, DynamoDB with boto3). API: Flask or FastAPI and load testing with Locust. Testing & Logging: PyTest and Logging. From here, you can already deploy on hosting services (Vercel, Render, Heroku). Build for scale: DevOps: Docker. Security: PyJWT, OAuth. CI/CD: Github Actions or Azure DevOps. Monitoring: Grafana + Prometheus for Python, add Alerting provisioning HTTP API to handle SRE automation. Packaging: PyPi, pip. Cache: functools or redis. At this stage (with good finance), considering choosing Kubernetes, or Cloud providers (AWS/GCP/Azure) to meet SLOs. Language optimization: Performance: Numba (JIT), Cython, PyPy, multiprocessing, consider list comprehension or numpy. Profiling: CProfile with SnakeViz Code analyzer: Pylint It’s worth noting that Python comes with a Global Interpreter Lock and is dynamically typed, which may lead to slower performance compared to Object-Oriented Programming (OOP) languages. Achieving further optimization would require considering the architecture of your software, system, and algorithms. However, if you find Python more convenient for development and are constrained by time to learn another language, achieving your goals is still possible. Will post more about my learning. #python #programming #devops
Nov 21, 2023	This portfolio is created. My goal is to have somewhere I can connect what I have learned together. I prefer my own website since I can customize the tags for my needs.

Jan 24, 2024

While Go, Rust, and JS are more popular or performance-wise for web servers, if I have to use Python only (since it is also popular for data science), here are what I am using already for almost any needs: General - Build a general website:

Web development: Django (+ HTML, CSS).
Backend: SQL + sqlite3, or NoSQL (ex, DynamoDB with boto3).
API: Flask or FastAPI and load testing with Locust.
Testing & Logging: PyTest and Logging.

From here, you can already deploy on hosting services (Vercel, Render, Heroku). Build for scale:

DevOps: Docker.
Security: PyJWT, OAuth.
CI/CD: Github Actions or Azure DevOps.
Monitoring: Grafana + Prometheus for Python, add Alerting provisioning HTTP API to handle SRE automation.
Packaging: PyPi, pip.
Cache: functools or redis.

At this stage (with good finance), considering choosing Kubernetes, or Cloud providers (AWS/GCP/Azure) to meet SLOs. Language optimization:

Performance: Numba (JIT), Cython, PyPy, multiprocessing, consider list comprehension or numpy.
Profiling: CProfile with SnakeViz
Code analyzer: Pylint

It’s worth noting that Python comes with a Global Interpreter Lock and is dynamically typed, which may lead to slower performance compared to Object-Oriented Programming (OOP) languages. Achieving further optimization would require considering the architecture of your software, system, and algorithms. However, if you find Python more convenient for development and are constrained by time to learn another language, achieving your goals is still possible. Will post more about my learning. #python #programming #devops

Nov 21, 2023

This portfolio is created. My goal is to have somewhere I can connect what I have learned together. I prefer my own website since I can customize the tags for my needs.

latest posts

Apr 17, 2024	How can backend developers get involved with AI? Let's talk about vector database index.
Feb 12, 2024	My thought process of building end-to-end low-cost backend
Nov 12, 2023	Good practices on writing Dockerfile