Certificates

 Here I'll try to document my self-learning journey that started in the Summer of 2019. I embarked on this journey after I decided to pivot careers into the wild world of Data. Most of these certificates were done through MOOC platforms, such as Coursera, and prior to me enrolling in Graduate school at Georgia Tech back in the winter of 2020... but I'll still take the time to explore some new ones from time to time. 

Google

• Preparing for Google Cloud Certification: Machine Learning Engineer Professional Certificate

  • • Launching into Machine Learning

• Intro to GenAI

  • • Generative AI Fundamentals

    • Introduction to Generative AI Studio

    • Attention Mechanism

    • Encoder-Decoder Architecture

    • Transformer Models and BERT Model

    • Create Image Captioning Models

    • Introduction to Image Generation

    • Introduction to Large Language Models

    • Introduction to Responsible AI

    • Cloud Vision API

• From Data to Insights with Google Cloud Platform Specialization

  • • Applying Machine Learning to your Data with GCP

    • Achieving Advanced Insights with BigQuery

    • Creating New BigQuery Datasets and Visualizing Insights

    • Exploring and Preparing your Data with BigQuery 

Tableau 

• Certified Data Analyst

  • • Early Bird (Beta Tester for the Certified Data Analyst Exam)

DeepLearning.AI 

• Natural Language Processing Specialization

  • • Natural Language Processing with Attention Models

    • Natural Language Processing with Sequence Models

    • Natural Language Processing with Probabilistic Models

    • Natural Language Processing with Classification and Vector Spaces

Cloudera 

• Modern Big Data Analysis with SQL Specialization

  • • Managing Big Data in Clusters and Cloud Storage

    • Analyzing Big Data with SQL

    • Foundations for Big Data Analysis with SQL

UC Davis

• SQL Basics for Data Science Specialization

  • • SQL for Data Science Capstone Project

    • SQL for Data Science

    • Distributed Computing with Spark SQL

    • Data Wrangling, Analysis and AB Testing with SQL

Macquarie University

• Excel Skills for Business Specialization

  • • Excel Skills for Business: Advanced

    • Excel Skills for Business: Intermediate II

    • Excel Skills for Business: Intermediate I

    • Excel Skills for Business: Essentials

University of Colorado at Boulder

• Advanced Business Analytics Specialization

  • • Advanced Business Analytics Capstone

    • Communicating Business Analytics Results

    • Business Analytics for Decision Making

    • Predictive Modeling and Analytics

    • Introduction to Data Analytics for Business

Duke University

• Java Programming and Software Engineering Fundamentals Specialization

  • • Java Programming: Build a Recommendation System

    • Java Programming: Arrays, Lists, and Structured Data

    • Programming Foundations with JavaScript, HTML, and CSS

    • Java Programming: Solving Problems with Software

    • Java Programming: Principles of Software Design

DeepLearning.AI

• Deep Learning with TensorFlow Specialization

  • Structuring Machine Learning Projects

  • Sequence Models

  • Neural Networks and Deep Learning

  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization  and Optimization

  • Convolutional Neural Networks

IBM

• Data Science Professional Certificate

  • Data Analysis with Python

  • Data Science Methodology

  • Machine Learning with Python

  • Data Visualization with Python

  • Tools for Data Science

  • Applied Data Science Capstone

  • Python for Data Science and AI

  • Databases and SQL for Data Science

  • What is Data Science?

UC Davis

• Data Visualization with Tableau Specialization

  • • Data Visualization with Tableau Project

    • Essential Design Principles for Tableau

    • Fundamentals of Visualization with Tableau

    • Creating Dashboards and Storytelling with Tableau

    • Visual Analytics with Tableau

AWS

• Machine Learning Path: Data Scientist

  • • Practical Data Science with Amazon SageMaker

    • Understanding Amazon EBS Volume Encryption

    • Protecting Your Instance with Security Groups

    • Differences Between Security Groups and NACLs

    • Authentication and Authorization with AWS Identity and Access Management

    • Machine Learning Security

    • AWS Security Fundamentals

    • Building Recommendation Systems with MXNet and GluOn

    • Anomaly Detection with AWS

    • Advanced Analytics with Amazon SageMaker

    • Automatic Model Tuning in Amazon SageMaker

    • Introduction to Amazon SageMaker Neo

    • Machine Learning Algorithms Explained

    • Introduction to Amazon SageMaker

    • Machine Learning Data Readiness

    • The Elements of Data Science

    • Data Science Capstone: Real World ML Decisions 

DataCamp

• Big Data with PySpark Track

  • • Introduction to PySpark

    • Big Data Fundamentals with PySpark

    • Cleaning Data with PySpark

    • Feature Engineering with PySpark

    • Machine Learning with PySpark

    • Building Recommendation Engines with PySpark

DataCamp

• Machine Learning Scientist with Python 

  • • Linear Classifiers in Python

    • Extreme Gradient Boosting with XGBoost

    • Clustering Methods with SciPy

    • Dimensionality Reduction in Python

    • Preprocessing for Machine Learning in Python

    • Machine Learning for Time Series Data in Python

    • Feature Engineering for Machine Learning in Python

    • Model Validation in Python

    • Introduction to Natural Language Processing in Python

    • Feature Engineering for NLP in Python

    • Introduction to TensorFlow in Python

    • Introduction to Deep Learning with Keras

    • Advanced Deep Learning with Keras

    • Image Processing in Python

    • Image Processing with Keras in Python

    • Hyperparameter Tuning in Python

    • Introduction to PySpark

    • Machine Learning with PySpark

DataCamp

• Data Scientist with R 

  • • Introduction to R

    • Intermediate R

    • Introduction to the Tidyverse

    • Data Manipulation with dplyr

    • Joining Data with dplyr

    • Introduction to Data Visualization with ggplot2

    • Intermediate Data Visualization with ggplot2

    • Introduction to Importing Data in R

    • Intermediate Importing Data in R

    • Working with Dates and Times in R

    • Introduction to Writing Functions in R

    • Data Cleaning in R

    • Exploratory Data Analysis in R

    • Case Study: Exploratory Data Analysis in R

    • Correlation and Regression in R

    • Supervised Learning in R: Regression

    • Supervised Learning in R: Classification

    • Unsupervised Learning in R

    • Cluster Analysis in R

DataCamp

• Data Scientist with Python

  • • Introduction to Python

    • Intermediate Python for Data Science

    • Python Data Science Toolbox (Part 1)

    • Python Data Science Toolbox (Part 2)

    • Importing Data in Python (Part 1)

    • Importing Data in Python (Part 2)

    • Cleaning Data in Python

    • pandas Foundations

    • Manipulating DataFrames with pandas

    • Merging DataFrames with pandas

    • Analyzing Police Activity with pandas

    • Intro to SQL for Data Science

    • Introduction to Relational Databases in SQL

    • Introduction to Data Visualization with Python

    • Interactive Data Visualization with Bokeh

    • Statistical Thinking in Python (Part 2)

    • Statistical Thinking in Python (Part 1)

    • Joining Data in SQL

    • Introduction to Shell for Data Science

    • Conda Essentials

    • Supervised Learning with scikit-learn

    • Machine Learning with the Experts: School Budgets

    • Machine Learning with Tree-Based Models in Python

    • Unsupervised Learning in Python

    • Introduction to Deep Learning in Python

Codecademy

• Learning C++