Genomic Data Science Specialization - Johns Hopkins University (Coursera)

This repository contains my completed code exercises for the Genomic Data Science Specialization offered by Johns Hopkins University on Coursera.
It covers 8 courses that together explore the tools, methods, and algorithms used in modern genomic research.`

Note: These solutions are for learning and reference purposes. Please adhere to the Coursera Honor Code if you're currently taking the course.

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Specialization Overview

The specialization consists of the following courses:

1. Introduction to Genomic Technologies
   • Overview of modern genomic research tools and technologies.
2. Python for Genomic Data Science
   • Python programming skills tailored to bioinformatics and genomics.
3. Algorithms for DNA Sequencing
   • Core algorithms for analyzing DNA sequences.
4. Command Line Tools for Genomic Data Science
   • Using Unix/Linux command line tools for genomic data analysis.
5. Bioconductor for Genomic Data Science
   • Introduction to the Bioconductor project in R for genomic research.
6. Statistics for Genomic Data Science
   • Statistical analysis and inference for genomics.
7. Genomic Data Science with Galaxy
   • Visual, web-based tools for genomic data analysis.
8. Capstone Project
   • Integration of skills to solve a real-world genomics problem.

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Week 1 - Overview

Course: 01 - Introduction to Genomic Technologies
Platform: Coursera - Johns Hopkins University
Specialization: Genomic Data Science

Topics Covered

• Just enough molecular biology
• The genome and DNA structure
• Central Dogma (transcription, translation)
• DNA modifications

Week 2 - Measurement Technology

• PCR basics, Next-generation sequencing (NGS), applications of sequencing

Week 3 - Computing Technology

• Foundations of computer science, algorithms, memory/data structures, computational biology software

Week 4 - Data Science Technology

• Reproducibility, statistical inference, experimental design, variation, inference

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Course 2: Python for Genomic Data Science:contentReference

Week 1 - First Steps in Python

• Python overview, basic programming, Jupyter notebooks

Week 2 - Data Structures, Ifs & Loops

Week 3 - Functions, Modules & Packages

Week 4 - Communicating with the Outside & Biopython