Jon-Ting / coursera-certifications

:zap: A repository to showcase my completed courses on the Coursera platform.

Coursera-Certifications

This is a repository to showcase my achievement in the courses I took/am taking for self-development on the Coursera platform. I have attempted to group the courses based on the data science Venn diagram shown below. The links to the courses (COURSE NAME) and certificates (CERT) are provided. Would appreciate comments on the grouping of the courses too if you have any better idea!

Professional Certificates

• DeepLearning.AI TensorFlow Developer (deeplearning.ai) (CERT)

  1. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (CERT)
  2. Convolutional Neural Networks in TensorFlow (CERT)
  3. Natural Language Processing in TensorFlow (CERT)
  4. Sequences, Time Series and Prediction (CERT)

• Google IT Automation with Python (Google) (CERT)

  1. Crash Course on Python (CERT)
  2. Using Python to Interact with the Operating System (CERT)
  3. Introduction to Git and GitHub (CERT)
  4. Troubleshooting and Debugging Techniques (CERT)
  5. Configuration Management and the Cloud (CERT)
  6. Automating Real-World Tasks with Python (CERT)

• Google IT Support (Google) (CERT)

  1. Technical Support Fundamentals (CERT)
  2. The Bits and Bytes of Computer Networking (CERT)
  3. Operating Systems and You: Becoming a Power User (CERT)
  4. System Administration and IT Infrastructure Services (CERT)
  5. IT Security: Defense against the digital dark arts (CERT)

• Data Engineering with Google Cloud (Google Cloud)

  • Data Engineering, Big Data, and Machine Learning on GCP Specialization (CERT)
    1. Google Cloud Platform Big Data and Machine Learning Fundamentals (CERT)
    2. Modernizing Data Lakes and Data Warehouses with GCP (CERT)
    3. Building Batch Data Pipelines on GCP (CERT)
    4. Building Resilient Streaming Analytics Systems on GCP (CERT)
    5. Smart Analytics, Machine Learning, and AI on GCP (CERT)
  • Preparing for the Google Cloud Professional Data Engineer Exam

• Cloud Architecture with Google Cloud (Google Cloud)

  • Cloud Engineering with Google Cloud (CERT)
    1. Google Cloud Platform Fundamentals: Core Infrastructure (CERT)
    2. Essential Google Cloud Infrastructure: Foundation (CERT)
    3. Essential Google Cloud Infrastructure: Core Services (CERT)
    4. Elastic Google Cloud Infrastructure: Scaling and Automation (CERT)
    5. Preparing for the Google Cloud Associate Cloud Engineer Exam (CERT)
  • Reliable Google Cloud Infrastructure: Design and Process
  • Preparing for the Google Cloud Professional Cloud Architect Exam

Specializations

(A) Computer Science

• Python 3 Programming (University of Michigan) (CERT)

  1. Python Basics (CERT)
  2. Python Functions, Files, and Dictionaries (CERT)
  3. Data Collection and Processing with Python (CERT)
  4. Python Classes and Inheritance (CERT)
  5. Python Project: pillow, tesseract, and opencv (CERT)

• Python for Everybody (University of Michigan) (CERT)

  1. Programming for Everybody (Getting Started with Python) (CERT)
  2. Python Data Structures (CERT)
  3. Using Python to Access Web Data (CERT)
  4. Using Databases with Python (CERT)
  5. Capstone: Retrieving, Processing, and Visualizing Data with Python (with Honors) (CERT)

• Introduction to Computer Science and Programming (University of London)

  1. Introduction to Computer Programming (CERT)
  2. How Computers Work (CERT)
  3. Mathematics for Computer Science

• Networking in Google Cloud (Google Cloud) (CERT)

  1. Google Cloud Platform Fundamentals: Core Infrastructure (CERT)
  2. Networking in Google Cloud: Defining and Implementing Networks (CERT)
  3. Networking in Google Cloud: Hybrid Connectivity and Network Management (CERT)

• AWS Fundamentals (AWS) (CERT)

  1. AWS Fundamentals: Going Cloud-Native (CERT)
  2. AWS Fundamentals: Addressing Security Risk (CERT)
  3. AWS Fundamentals: Migrating to the Cloud (CERT)
  4. AWS Fundamentals: Building Serverless Applications (CERT)

(B) Mathematics & Statistics

• Mathematics for Machine Learning (Imperial College London) (CERT)

  1. Mathematics for Machine Learning: Linear Algebra (CERT)
  2. Mathematics for Machine Learning: Multivariate Calculus (CERT)
  3. Mathematics for Machine Learning: PCA (CERT)

• Statistics with Python (University of Michigan) (CERT)

  1. Understanding and Visualizing Data with Python (CERT)
  2. Inferential Statistical Analysis with Python (CERT)
  3. Fitting Statistical Models to Data with Python (CERT)

• Introduction to Discrete Mathematics for Computer Science (National Research University Higher School of Economics)

  1. Mathematical Thinking in Computer Science
  2. Combinatorics and Probability
  3. Introduction to Graph Theory
  4. Number Theory and Cryptography
  5. Delivery Problem

(C) Domain Expertise

(A ∩ B) Machine Learning

• Machine Learning (University of Washington) (CERT)

  1. Machine Learning Foundations: A Case Study Approach (CERT)
  2. Machine Learning: Regression (CERT)
  3. Machine Learning: Classification (CERT)
  4. Machine Learning: Clustering & Retrieval (CERT)

• Deep Learning (deeplearning.ai) (CERT)

  1. Neural Networks and Deep Learning (CERT)
  2. Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (CERT)
  3. Structuring Machine Learning Projects (CERT)
  4. Convolutional Neural Networks (CERT)
  5. Sequence Models (CERT)

• Machine Learning with TensorFlow on Google Cloud Platform (Google Cloud) (CERT)

  1. How Google does Machine Learning (CERT)
  2. Launching into Machine Learning (CERT)
  3. Introduction to TensorFlow (CERT)
  4. Feature Engineering (CERT)
  5. Art and Science of Machine Learning (CERT)

• Machine Learning: Algorithms in the Real World (Alberta Machine Intelligence Institute) (CERT)

  1. Introduction to Applied Machine Learning (CERT)
  2. Machine Learning Algorithms: Supervised Learning Tip to Tail (CERT)
  3. Data for Machine Learning (CERT)
  4. Optimizing Machine Learning Performance (CERT)

• Advanced Machine Learning (National Research University Higher School of Economics)

  1. Introduction to Deep Learning
  2. How to Win a Data Science Competition: Learn from Top Kagglers
  3. Bayesian Methods for Machine Learning
  4. Practical Reinforcement Learning
  5. Deep Learning in Computer Vision
  6. Natural Language Processing
  7. Addressing Large Hadron Collider Challenges by Machine Learning

• Advanced Machine Learning with TensorFlow on Google Cloud Platform (Google Cloud) (CERT)

  1. End-to-End Machine Learning with TensorFlow on GCP (CERT)
  2. Production Machine Learning Systems (CERT)
  3. Image Understanding with TensorFlow on GCP (CERT)
  4. Sequence Models for Time Series and Natural Language Processing (CERT)
  5. Recommendation Systems with TensorFlow on GCP (CERT)

• Machine Learning for Everyone with Eric Siegel (SAS) (CERT)

  1. The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats (CERT)
  2. Launching Machine Learning: Delivering Operational Success with Gold Standard ML Leadership (CERT)
  3. Machine Learning Under the Hood: The Technical Tips, Tricks, and Pitfalls (CERT)

(B ∩ C) Research

• Data Analysis and Interpretation (Wesleyan Univeristy)
  1. Data Management and Visualization (CERT)
  2. Data Analysis Tools (CERT)
  3. Regression Modeling in Practice
  4. Machine Learning for Data Analysis
  5. Data Analysis and Interpretation Capstone

(A ∩ C) Software Development

• Python Data Products for Predictive Analytics (University of California San Diego)
  1. Basic Data Processing and Visualization (CERT)
  2. Design Thinking and Predictive Analytics for Data Products (CERT)
  3. Meaningful Predictive Modeling (CERT)
  4. Deploying Machine Learning Models

(A ∩ B ∩ C) Data Science

• Advanced Data Science with IBM (IBM)

  1. Fundamentals of Scalable Data Science (CERT)
  2. Advanced Machine Learning and Signal Processing (CERT)
  3. Applied AI with Deep Learning (CERT)
  4. Advanced Data Science Capstone

• Data Science (Johns Hopkins University) (CERT)

  • Data Science: Foundations using R (CERT)
    1. The Data Scientist’s Toolbox (CERT)
    2. R Programming (CERT)
    3. Getting and Cleaning Data (CERT)
    4. Exploratory Data Analysis (CERT)
    5. Reproducible Research (CERT)
  • Data Science: Statistics and Machine Learning (CERT)
    1. Statistical Inference (CERT)
    2. Regression Models (CERT)
    3. Practical Machine Learning (CERT)
    4. Developing Data Products (CERT)
    5. Data Science Capstone (CERT)

• Applied Data Science with Python (University of Michigan) (CERT)

  1. Introduction to Data Science in Python (CERT)
  2. Applied Plotting, Charting & Data Representation in Python (CERT)
  3. Applied Machine Learning in Python (CERT)
  4. Applied Text Mining in Python (CERT)
  5. Applied Social Network Analysis in Python (CERT)

• Executive Data Science (Johns Hopkins University) (CERT)

  1. A Crash Course in Data Science (CERT)
  2. Building a Data Science Team (CERT)
  3. Managing Data Analysis (CERT)
  4. Data Science in Real Life (CERT)
  5. Executive Data Science Capstone (CERT)

• From Data to Insights with Google Cloud Platform (Google Cloud) (CERT)

  1. Exploring and Preparing your Data with BigQuery (CERT)
  2. Creating New BigQuery Datasets and Visualizing Insights (CERT)
  3. Achieving Advanced Insights with BigQuery (CERT)
  4. Applying Machine Learning to your Data with GCP (CERT)

Courses

(A) Computer Science

• Python Programming Essentials (Rice University) (CERT)
• Getting started with TensorFlow 2 (Imperial College London) (CERT)
• Cloud Computing Basics (Cloud 101) (LearnQuest) (CERT)
• The Unix Workbench (Johns Hopkins University) (CERT)

(B) Mathematics & Statistics

• Bayesian Statistics: From Concept to Data Analysis (with Honors) (University of California, Santa Cruz) (CERT)
• Data Science Math Skills (Duke University) (CERT)

(C) Domain Expertise

• Computational Vision (University of Colorado Boulder) (CERT)
• Nanotechnology: A Maker’s Course (Duke University, North Carolina State University, The University of North Carolina at Chapel Hill) (CERT)

(A ∩ B) Machine Learning

• Machine Learning (Stanford University) (CERT)
• Machine Learning for All (University of London) (CERT)
• Customising your models with TensorFlow 2 (Imperial College London) (CERT)
• Getting Started with AWS Machine Learning (Amazon Web Services) (CERT)
• An Introduction to Practical Deep Learning (Intel) (CERT)
• Introduction to Machine Learning (Duke University) (CERT)
• AI For Everyone (deeplearning.ai) (CERT)
• Machine Learning for Business Professionals (Google Cloud) (CERT)

(B ∩ C) Research

• Computational Neuroscience (University of Washington) (CERT)
• Materials Data Sciences and Informatics (Georgia Institute of Technology) (CERT)

(A ∩ C) Software Development

• Google Cloud Product Fundamentals (Google Cloud) (CERT)

(A ∩ B ∩ C) Data Science

• Code Free Data Science (University of California San Diego) (CERT)

Guided Projects (Coursera Project Network)

(A) Computer Science

Database

• Introduction to Relational Database and SQL (CERT)
• Creating Database Tables with SQL (CERT)
• Beginning SQL Server (CERT)
• Database Design and Diagramming in Dia (CERT)
• Create Customer Support Data with Google Sheets (CERT)
• Spreadsheets for Beginners using Google Sheets (CERT)

Visualisation

• Computer Vision - Image Basics with OpenCV and Python (CERT)
• Data Visualization with Plotly Express (CERT)
• Analyze Box Office Data with Plotly and Python (CERT)
• Create Informative Presentations with Google Slides (CERT)

Web Development & Graphics Design

• RESTful API with HTTP and JavaScript (CERT)
• Develop a Company Website with Wix (CERT)
• Create a Business Marketing Brand Kit Using Canva (CERT)
• Use Canva to Create Social Media Marketing Designs (CERT)

Version Control

• Git for Developers Using Github (CERT)

Programming Language

• Object-Oriented Programming with Java (CERT)

Data Processing and Analysis

• Processing Data with Python (CERT)
• Exploratory Data Analysis with Seaborn (CERT)
• Image Data Augmentation with Keras (CERT)
• Building Custom Regional Reports with Google Analytics (CERT)
• Build Data Analysis and Transformation Skills in R using DPLYR (CERT)

(B) Mathematics & Statistics

• Intro to Time Series Analysis in R (CERT)

(C) Domain Expertise

• Google Ads for Beginners (CERT)

(A ∩ B) Machine Learning

Supervised

Classification

Neural Network

• Basic Image Classification with TensorFlow (CERT)
• Neural Network from Scratch in TensorFlow (CERT)
• Classification with Transfer Learning in Keras (CERT)
• Real-time OCR and Text Detection with Tensorflow, OpenCV and Tesseract (CERT)
• Perform Real-Time Object Detection with YOLOv3 (CERT)
• Siamese Network with Triplet Loss in Keras (CERT)
• Facial Expression Recognition with Keras (CERT)
• Image Classification with CNNs using Keras (CERT)
• Build a Deep Learning Based Image Classifier with R (CERT)
• Classify Radio Signals from Space using Keras (CERT)
• Traffic Sign Classification Using Deep Learning in Python/Keras (CERT)
• Machine Learning: Predict Numbers from Handwritten Digits using a Neural Network, Keras, and R (CERT)
• Machine Learning: Create a Neural Network that Predicts whether an Image is a Car or Airplane (CERT)

Logistic Regression

• Logistic Regression with NumPy and Python (CERT)
• Perform Sentiment Analysis with scikit-learn (CERT)
• Evaluate Machine Learning Models with Yellowbrick (CERT)

Support Vector Machines

• Support Vector Machines in Python, From Start to Finish (CERT)
• Support Vector Machines with scikit-learn (CERT)

Tree-Based Models

• Classification Trees in Python, From Start To Finish (CERT)
• Predict Employee Turnover with scikit-learn (CERT)
• Predict Diabetes with a Random Forest using R (CERT)

Regression

• Linear Regression with Python (CERT)
• Linear Regression with NumPy and Python (CERT)
• Multiple Linear Regression with scikit-learn (CERT)
• Predicting House Prices with Regression using TensorFlow (CERT)
• Predicting Salaries with Simple Linear Regression in R (CERT)

Unsupervised

• Machine Learning Feature Selection in Python (CERT)
• Dimensionality Reduction using an Autoencoder in Python (CERT)
• Principal Component Analysis with NumPy (CERT)
• Image Compression with K-Means Clustering (CERT)
• Clustering Geolocation Data Intelligently in Python (CERT)
• Unsupervised Machine Learning for Customer Market Segmentation (CERT)

Semi-Supervised

• Image Noise Reduction with Auto-encoders using TensorFlow (CERT)
• Image Denoising Using AutoEncoders in Keras and Python (CERT)
• Image Super Resolution Using Autoencoders in Keras (CERT)
• Generate Synthetic Images with DCGANs in Keras (CERT)

(B ∩ C) Research

(A ∩ C) Software Development

• Neural Network Visualizer Web App with Python (CERT)
• Build a Machine Learning Web App with Streamlit and Python (CERT)
• Build a Data Science Web App with Streamlit and Python (CERT)

(A ∩ B ∩ C) Data Science

• Custom Prediction Routine on Google AI Platform (CERT)
• Automatic Machine Learning with H2O AutoML and Python (CERT)
• Machine Learning with H2O Flow (CERT)
• Predictive Analytics for Business with H2O in R (CERT)
• Machine Learning Pipelines with Azure ML Studio (CERT)
• Predictive Modelling with Azure Machine Learning Studio (CERT)
• Deep Learning Inference with Azure ML Studio (CERT)
• AutoML for Computer Vision with Microsoft Custom Vision (CERT)
• Data Analytics: Scraping Data using Hadley Wickam's Rvest package in R (CERT)