Skills
Courses
University of California, Santa Cruz
Bachelor of Science (BS): Computer Engineer
- Mechatronics
- Machine Learning (Deep Learning)
- Deep Neural Networks Graduate Seminar
- Operating System (C programming)
- Computer Systems and Assembly Language
- Logic Design (Xilinx)
- Computer Architecture
- Intro to Circuits
- Applied Discrete Mathematics
- Introduction to Data Structures (Java and C)
- Microprocessor System Design Laboratory (C programming)
- Probability and Statistics for Engineers
- Mobile Sensing and Interaction (Objective-C)
- Differential Equations
- Algorithms and Abstract Data Types (C and Java)
- Verilog
- Advanced Programming (C++)
- Micro-Electro-Mechanical Systems Optics Seminar
- Accelerated Introduction to Programming (Java)
- Signals and Systems
- Linear Algebra
Certificates
This course will teach you how to get started with AWS Machine Learning. Key topics
include: Machine Learning on AWS, Computer Vision on AWS, and Natural Language Processing
(NLP) on AWS. Each topic consists of several modules deep-diving into variety of ML
concepts, AWS services as well as insights from experts to put the concepts into practice.
- Understand what WebAssembly is and how it speeds up the web
- Use native JavaScript APIs to load and run WebAssembly modules
- Learn to use Emscripten and compile your own C or C++ code as a WebAssembly module
- Use WebAssembly in a real-world project and micro benchmark
JavaScript and programming fundamentals: variables, boolean logic, if/else, loops,
functions, arrays, etc. Complex features like the 'this' keyword, function constructors,
prototypal inheritance, first-class functions, closures Asynchronous JavaScript: The
event loop, promises, async/await, AJAX and APIs Modern JavaScript for 2020: NPM, Webpack,
Babel and ES6 modules A true understanding of how JavaScript works behind the scenes What's
new in ES6: arrow functions, classes, default and rest parameters, etc. Practice your new
skills with coding challenges (solutions included) Organize and structure your code using
JavaScript patterns like modules.
- Natours Project - Setup and First Steps (Part 1)
- How CSS works: A Look behind the scenes
- Introduction to Sass and NPM
- Natours Project - Using Advanced CSS and Sass (Part 2)
- Natours Project - Advanced Responsive Design (Part 3)
- Trillo Project - Mastrer Flexbox
- A Quick Introduction to CSS Grid Layouts
- Natours Project - Master CSS Grid Layouts!
- Introducition to Cross-Platforem Development with Flutter and Dart
- Set and Installing
- I am Rich - How to Create Flutter Apps from Scratch
- Running Your App on a Physical Device
- I Am Poor - App Challenge
- MiCard - How to Build Beautiful UIs with Flutter Widgets
- Dicee - Building Apps with State
- Boss Level Challenge 1 - Magic 8 Ball
- Xylophone - Using Flutter and Dart Packages to Speed Up Development
- Quizzler - Modularising & Oeganising Flutter Code
- Boss Level Challenge 2 - Destini
- BMI Calculator - Builing Flutter UI for Intermediates
- Clima - Powering Your Flutter App with Live Web Data
- Boss Level Challenge 3 - Bitcoin Ticker
- Flash Chat - Flutter x Firebase CLoud Firestore
- Flutter State Management
- Basics of Computer Vision and OpenCV
- Image Manipulations & Processing
- Image Segmentation & Contours
- Object Detection in OpenCV
- Object Detection - Build a Face, People and Car/Vehicle Detector
- HAAR Cascade Classifiers
- Augmented Reality (AR) - Facial Landmark Identification
- Simple Machine Learning using OpenCV
- Object Tracking & Motion Analysis
- Computational Photography
- Deep Learning: Computer Vision
- Neural Style Transfer with OpenCV
- Object Detection - Use SSDs
- Colorize Black and White Images
- Python Crash Course (Optional)
- NumPy Crash Course (Optional)
- Computer Vision: Finding Lane Lines
- The Perceptron
- Keras
- Deep Neural Networks
- Multiclass Classification
- MNIST Image Recognition
- Convolutional Neural Networks
- Classifying Road Symbols
- Polynomial Regression
- Behavioural Cloning
Accelerating my deep learning skills with PyTorch covering
all the fundamentals of deep learning with a python-first framework.
- PyTorch Fundamentals: Matrices
- PyTorch Fundamentals: Variables and Gradients
- Linear Regression with PyTorch
- Logistic Regression with PyTorch
- Feedforward Neural Network with PyTorch
- Convolutional Neural Network (CNN) with PyTorch
- Recurrent Neural Networks (RNN)
- Long Short-Term Memory Networks (LSTM)
- Convolutional Neural Networks
- Classifying Road Symbols
- Polynomial Regression
- Behavioural Cloning
- Tensorflow Basics
- Introduction to Neural Networks
- Convolutional Neural Network
- Recurrent Neural Network (LSTM & GRU)
- Word2Vec Theory (Word Embeddings)
- Miscellaneous Topics (Keras: layers, Estimator)
- AutoEncoders and Unlabled data
- Dimensionality Reduction with Linear Autoencoder
- Reinforcement Learning with OpenAI Gym
- Generative Advasaral Network
- Research outside CNN: Resnet, VGG16, Mask RCNN
- Research outside GAN: StackGan, AttnGan, Wavenet
- Research outside Deep Reinforcement Learning: AlphaGo
- Research outside Unsupervised Learning: Restricted Boltzman Machine
I learned to build cross-platform iOS and Android apps in
HTML/CSS/JavaScript with Ionic Framework, AngularJS and Cordova.
- AngularJS controller and $http service Preview
- Ionic List component
- Importing other JavaScript libraries
- Infinite scroll and pull-to-refresh
- Adding Cordova plugins: the InAppBrowser
- Basic navigation and routing
- State parameters and forms
- Reusing the same view for multiple states
- Creating a new AngularJS service and module
- Saving data in Local Storage
- Swipe to reveal
- Ionicons
- List reordering
- ngCordova
- Camera plugin
- Geolocation plugin and Google Maps
- Cordova's config.xml file
Other Skills
Programming Skills
- 4 year experience: C/C++ • OpenCV • Java • JavaScript • C with PSoC Creator
- 2 year experience: C++ • Matlab • Swift 2.1 • HTML5 • CSS3 • Assembly • LATEX • Angular JS • ionic framework
- 1 Year Experience: Objective-C • Verilog • Node JS • MongoDB • Express JS
Communication Skills
Can speak English (C1 self-assessment) and Spanish (Limited working proficiency).
Experienced in tutoring and lecturing (spoke at a engineering mentorship program).