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coursera's Introduction

Coursera

This repository contains my coursework for various courses/specializations I completed (or currently taking) on Coursera

Specialization: Machine Learning Engineering for Production (MLOps)

Courses:

  1. Introduction to Machine Learning in Production
  2. Machine Learning Data Lifecycle in Production
  3. Machine Learning Modeling Pipelines in Production
  4. Deploying Machine Learning Models in Production
    • Certificate: Ongoing

Specialization: Deep Learning

Certificate: https://www.coursera.org/account/accomplishments/specialization/certificate/95A5RPFS8YQT

Courses:

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

Specialization: Mathematics for Data Science

Certificate: https://www.coursera.org/account/accomplishments/specialization/certificate/B7WTZN4URXDP

Courses:

  1. Discrete Math and Analyzing Social Graphs
  2. Calculus and Optimization for Machine Learning
  3. First Steps in Linear Algebra for Machine Learning
  4. Probability Theory, Statistics and Exploratory Data Analysis

Course: Machine Learning

Course: Introduction to numerical analysis

Course: Introduction to Ordinary Differential Equations

Course: SQL for Data Science

Course: Fundamentals of Scalable Data Science

Specialization: Data Structures and Algorithms

Courses:

  1. Algorithm Toolbox
  2. Data Structures
  3. Algorithms on Graphs (TODO)
  4. Algorithms on Strings (TODO)
  5. Advanced Algorithms and Complexity (TODO)
  6. Genome Assembly Programming Challenge (TODO)

Specialization: Software Design and Architecture Specialization

  1. Object-Oriented Design
  2. Design Patterns (TODO)
  3. Software Architecture (TODO)
  4. Service-Oriented Architecture (TODO)

Specialization: Full Stack Web Development

Courses:

  1. HTML, CSS and JavaScript (Audited)
  2. Front-End Web UI Frameworks and Tools (Audited)

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