Online STEM Certificates

This repository showcases my professional certificates, specializations, online courses, and guided projects completed to expand and reinforce my theoretical and practical knowledge in science, mathematics, and computer science. It reflects my continuous learning journey and hands-on experience across STEM disciplines, which I attempt to classify with the aid of the following Venn diagram. This will be an ever-evolving endeavor.

Note

Both the conception of this publication and its structure are derived from Mr. Jon Ting's repository.

Moreover, I owe a debt of gratitude to the following instructors, each of whom has played a crucial role in shaping my skills: Mr. Ari Anastassiou, Mr. Snehan Kekre, Mr. Ryan Ahmed, Ms. Leire Ahedo, Mr. Amit Yadav, Mr. Andrew Ng, and Mr. Laurence Moroney.

To provide clarity, the following descriptions represent the consensus regarding the certificates outlined in this repository:

Professional Certificate: a series of related courses focused on providing hands-on experience in a skill.

Specialization: a series of related courses designed to help you master a specific topic.

Course: a structured educational program encompassing lessons, assignments, and discussions to impart knowledge and skills on a specific subject.

Guided Project: a hands-on educational experience focused on teaching a single skill or technique through step-by-step instruction and practice followed by a quiz.

Warning

There is a possibility that the classification of certain certificates may be inaccurate. Likewise, the subdivision of specific areas could be inaccurate or redundant. Should you have any insights or recommendations for improvement in either of these aspects, I would greatly appreciate your input.

On a different note, links have a tendency to rot over time. Therefore, if you come across any indications of decay in this repository, please do let me know.

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Professional Certificates

• DeepLearning.AI TensorFlow Developer (80 h) (deeplearning.ai) (CERT)

  1. Convolutional Neural Networks in TensorFlow (16 h) (CERT)
  2. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (18 h) (CERT)
  3. Natural Language Processing in TensorFlow (24 h) (CERT)
  4. Sequences, Time Series and Prediction (22 h) (CERT)

• Google Data Analytics (186 h) (Google) (CERT)

  1. Analyze Data to Answer Questions (26 h) (CERT)
  2. Ask Questions to Make Data-Driven Decisions (21 h) (CERT)
  3. Data Analysis with R Programming (36 h) (CERT)
  4. Foundations: Data, Data, Everywhere (22 h) (CERT)
  5. Google Data Analytics Capstone: Complete a Case Study (9 h) (CERT)
  6. Prepare Data for Exploration (25 h) (CERT)
  7. Process Data from Dirty to Clean (23 h) (CERT)
  8. Share Data Through the Art of Visualization (24 h) (CERT)

• Google Advanced Data Analytics (165 h) (Google) (CERT)

  1. Foundations of Data Science (23 h) (CERT)
  2. Get Started with Python (30 h) (CERT)
  3. Go Beyond the Numbers: Translate Data into Insights (32 h) (CERT)
  4. Google Advanced Data Analytics Capstone (9 h) (CERT)
  5. Regression Analysis: Simplify Complex Data Relationships (34 h) (CERT)
  6. The Nuts and Bolts of Machine Learning (37 h) (CERT)
  7. The Power of Statistics (37 h) (CERT)

• Google Professional Workspace Administrator (18 h) (Google Cloud) (CERT)

  1. Google Workspace Mail Management (4 h) (CERT)
  2. Google Workspace Security (4 h) (CERT)
  3. Introduction to Google Workspace Administration (4 h) (CERT)
  4. Managing Google Workspace (5 h) (CERT)
  5. Planning for a Google Workspace Deployment (1 h) (CERT)

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Specializations

(A) - Computer Science

• TensorFlow: Advanced Techniques (90 h) (deeplearning.ai) (CERT)

  1. Advanced Computer Vision with TensorFlow (19 h) (CERT)
  2. Custom and Distributed Training with TensorFlow (24 h) (CERT)
  3. Custom Models, Layers, and Loss Functions with TensorFlow (31 h) (CERT)
  4. Generative Deep Learning with TensorFlow (16 h) (CERT)

(B) - Mathematics & Statistics

• Mathematics for Machine Learning and Data Science (74 h) (deeplearning.ai) (CERT)

  1. Calculus for Machine Learning and Data Science (25 h) (CERT)
  2. Linear Algebra for Machine Learning and Data Science (21 h) (CERT)
  3. Probability & Statistics for Machine Learning & Data Science (28 h) (CERT)

(C) - Domain Expertise

• AI for Good (34 h) (deeplearning.ai) (CERT)

  1. AI and Climate Change (14 h) (CERT)
  2. AI and Disaster Management (11 h) (CERT)
  3. AI and Public Health (9 h) (CERT)

• Chemical Hazards and Process Safety Specialization (35 h) (University of California, Davis) (CERT)

  1. Chemical Hazards: Toxicology & Reactivity (8 h) (CERT)
  2. Fire and Explosion Hazards Analysis (7 h) (CERT)
  3. Introduction to Process Safety and Risk Analysis (8 h) (CERT)
  4. Predictive Models for Toxic Chemical Releases (12 h) (CERT)

• Mind and Machine (35 h) (University of Colorado Boulder) (CERT)

  1. Computational Vision (8 h) (CERT)
  2. Interpersonal, Developmental, and Evolutionary Perspectives of the Mind (12 h) (CERT)
  3. Methods for Solving Problems (6 h) (CERT)
  4. What is “the mind” and what is artificial intelligence? (7 h) (CERT)

(A ∩ B) - Machine Learning

• AI for Medicine (71 h) (deeplearning.ai) (CERT)

  1. AI for Medical Diagnosis (20 h) (CERT)
  2. AI for Medical Prognosis (29 h) (CERT)
  3. AI for Medical Treatment (22 h) (CERT)

• Deep Learning for Healthcare (62 h) (University of Illinois) (CERT)

  1. Advanced Deep Learning Methods for Healthcare (16 h) (CERT)
  2. Deep Learning Methods for Healthcare (22 h) (CERT)
  3. Health Data Science Foundation (24 h) (CERT)

• Deep Learning (125 h) (deeplearning.ai) (CERT)

  1. Convolutional Neural Networks (35 h) (CERT)
  2. Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization (23 h) (CERT)
  3. Neural Networks and Deep Learning (24 h) (CERT)
  4. Structuring Machine Learning Projects (6 h) (CERT)
  5. Sequence Models (37 h) (CERT)

• Machine Learning (94 h) (deeplearning.ai, Stanford University) (CERT)

  1. Advanced Learning Algorithms (34 h) (CERT)
  2. Supervised Machine Learning: Regression and Classification (33 h) (CERT)
  3. Unsupervised Learning, Recommenders, Reinforcement Learning (27 h) (CERT)

• Natural Language Processing (121 h) (deeplearning.ai) (CERT)

  1. Natural Language Processing with Attention Models (35 h) (CERT)
  2. Natural Language Processing with Classification and Vector Spaces (33 h) (CERT)
  3. Natural Language Processing with Probabilistic Models (30 h) (CERT)
  4. Natural Language Processing with Sequence Models (23 h) (CERT)

• Natural Language Processing (45 h) (Universidad Austral) (CERT)

  1. Introduction to natural language processing (13 h) (CERT)
  2. Data cleansing for natural language processing (12 h) (CERT)
  3. NLP Models and Algorithms (10 h) (CERT)
  4. NLP System Architecture and Dev-Ops (10 h) (CERT)

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Courses

(C) Domain Expertise

• Hexavalent Chromium: Regulations, Risks, and Sustainability (3 h) (Coursera) (CERT)
• Industrial Biotechnology (11 h) (The University of Manchester) (CERT)
• Nanotechnology: A Maker’s Course (26 h) (Duke University) (CERT)
• Protecting the World: Introducing Corrosion Science and Engineering (11 h) (University of Manchester) (CERT)
• Water: an essential resource (3 h) (Politecnico di Milano) (CERT)

(A ∩ B ∩ C) - Data Science

• Algorithms for DNA Sequencing (12 h) (Johns Hopkins University) (CERT)
• Introduction to Genomic Technologies (6 h) (Johns Hopkins University) (CERT)
• Python for Genomic Data Science (8 h) (Johns Hopkins University) (CERT)

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Guided Projects

(A) - Computer Science

Version Control

• Git for Developers Using Github (2 h) (CERT)

Data Analysis and Visualization

• Advanced Data Visualization with Python (1 h) (CERT)
• Analyze Text Data with Yellowbrick (1 h) (CERT)
• Data visualization with Seaborn (1 h) (CERT)
• Hyperparameter Tuning with Neural Network Intelligence (1 h) (CERT)
• Image Data Augmentation with Keras (1 h) (CERT)
• Python for Data Visualization: Matplotlib & Seaborn (Enhanced) (2 h) (CERT)
• Save, Load and Export Models with Keras (1 h) (CERT)

(C) Domain Expertise

• Python for Finance: Beta and Capital Asset Pricing Model (1 h) (CERT)
• Introduction to Customer Segmentation in Python (2 h) (CERT)

(A ∩ B) - Machine Learning

Supervised

• AI-Powered Chest Disease Detection and Classification (2 h) (CERT)
• Avoid Overfitting Using Regularization in TensorFlow (1 h) (CERT)
• Bank Loan Approval Prediction With Artificial Neural Nets (1 h) (CERT)
• Basic Sentiment Analysis with TensorFlow (1 h) (CERT)
• Cervical Cancer Risk Prediction Using Machine Learning (1 h) (CERT)
• Convolutional neural networks with Keras (2 h) (CERT)
• Convolutions for Text Classification with Keras (1 h) (CERT)
• Create Custom Layers in Keras (1 h) (CERT)
• Creating a NLM with Spacy (1 h) (CERT)
• Creating Custom Callbacks in Keras (1 h) (CERT)
• Creating Multi Task Models With Keras (1 h) (CERT)
• Deep-Dive into Tensorflow Activation Functions (1 h) (CERT)
• Diabetes Disease Detection with XG-Boost and Neural Networks (2 h) (CERT)
• Diabetic Retinopathy Detection with Artificial Intelligence (1 h) (CERT)
• Emotion AI: Facial Key-points Detection (2 h) (CERT)
• English/French Translator: Long Short Term Memory Networks (1 h) (CERT)
• Explainable AI: Scene Classification and GradCam Visualization (1 h) (CERT)
• Facial Expression Classification Using Residual Neural Nets (1 h) (CERT)
• Fake Instagram Profile Detector (1 h) (CERT)
• Fake News Detection with Machine Learning (1 h) (CERT)
• Fine-tuning Convolutional Networks to Classify Dog Breeds (2 h) (CERT)
• Imbalanced-learn ML models with unbalanced data (2 h) (CERT)
• Language Classification with Naive Bayes in Python (1 h) (CERT)
• Machine learning for time series with ARIMA, SARIMA... (2 h) (CERT)
• Machine Learning with Python. Advanced Level (2 h) (CERT)
• Machine Learning with Python. Intermediate level (2 h) (CERT)
• Malaria parasite detection using ensemble learning in Keras (1 h) (CERT)
• Mining Quality Prediction Using Machine & Deep Learning (1 h) (CERT)
• ML Parameters Optimization: GridSearch, Bayesian, RandomSearch (1 h) (CERT)
• Naive Bayes 101: Resume Selection with Machine Learning (1 h) (CERT)
• Named Entity Recognition using LSTMs with Keras (1 h) (CERT)
• Predict Ad Clicks Using Logistic Regression and XG-Boost (1 h) (CERT)
• Simple Recurrent Neural Network with Keras (1 h) (CERT)
• TensorFlow for CNNs: Learn and Practice CNNs (2 h) (CERT)
• Time Series with Deep Learning (RNN, LSTM) and Prophet (3 h) (CERT)
• Titanic Survival Prediction Using Machine Learning (2 h) (CERT)
• Tweet Emotion Recognition with TensorFlow (1 h) (CERT)
• Understanding Deepfakes with Keras (1 h) (CERT)

Neural Network

• Basic Image Classification with TensorFlow (2 h) (CERT)
• Classification with Transfer Learning in Keras (1 h) (CERT)
• Classify Radio Signals from Space using Keras (1 h) (CERT)
• Deep Learning Complete Course (2 h) (CERT)
• Facial Expression Recognition with Keras (2 h) (CERT)
• Image Classification with CNNs using Keras (1 h) (CERT)
• Neural Network from Scratch in TensorFlow (1 h) (CERT)
• Siamese Network with Triplet Loss in Keras (1 h) (CERT)
• Traffic Sign Classification Using Deep Learning in Python/Keras (1 h) (CERT)

Logistic Regression

• Logistic Regression with NumPy and Python (1 h) (CERT)
• Logistic Regression with Python and Numpy (1 h) (CERT)
• Perform Sentiment Analysis with scikit-learn (1 h) (CERT)

Support Vector Machines

• Support Vector Machines in Python, From Start to Finish (1 h) (CERT)
• Support Vector Machines with scikit-learn (2 h) (CERT)

Tree-Based Models

• Classification Trees in Python, From Start To Finish (1 h) (CERT)
• Machine Learning for Kyphosis Disease Classification (1 h) (CERT)
• Predict Employee Turnover with scikit-learn (1 h) (CERT)

Regression

• Linear Regression with NumPy and Python (1 h) (CERT)
• Linear Regression with Python (1 h) (CERT)
• Medical Insurance Premium Prediction with Machine Learning (2h) (CERT)
• Multiple Linear Regression with scikit-learn (1 h) (CERT)
• Predicting House Prices with Regression using TensorFlow (1 h) (CERT)
• Regression with Automatic Differentiation in TensorFlow (1 h) (CERT)
• Simple and multiple linear regression in Python (2 h) (CERT)

Unsupervised

• Autoencoders and extremely infrequent events (2 h) (CERT)
• Classification of Satellite data with autoML and Pycaret (2 h) (CERT)
• Clustering Geolocation Data Intelligently in Python (1 h) (CERT)
• Creating a Wordcloud using NLP and TF-IDF in Python (2 h) (CERT)
• Dimensionality Reduction using an Autoencoder in Python (1 h) (CERT)
• Exploring NLP with NLTK (1 h) (CERT)
• Image Compression with K-Means Clustering (1 h) (CERT)
• Interactive Word Embeddings using Word2Vec and Plotly (2 h) (CERT)
• K-Means Clustering 101: World Happiness Report (1 h) (CERT)
• Neural Style Transfer with TensorFlow (1 h) (CERT)
• Principal Component Analysis with NumPy (1 h) (CERT)
• Recognizing Shapes in Images with OpenCV (1 h) (CERT)
• Unsupervised Machine Learning for Customer Market Segmentation (1 h) (CERT)

Semi-Supervised

• Generate Synthetic Images with DCGANs in Keras (1 h) (CERT)
• Image Denoising Using AutoEncoders in Keras and Python (1 h) (CERT)
• Image Noise Reduction with Auto-encoders using TensorFlow (1 h) (CERT)
• Image Super Resolution Using Autoencoders in Keras (1 h) (CERT)

(A ∩ B ∩ C) - Data Science

• Complete Data Science Course (2 h) (CERT)
• Evaluate Machine Learning Models with Yellowbrick (1 h) (CERT)
• Perform Feature Analysis with Yellowbrick (2 h) (CERT)
• Regression Analysis with Yellowbrick (1 h) (CERT)