https://github.com/shuyib/mentorship-workflow
This is a repository I give to individuals interested in practical data science and machine learning
https://github.com/shuyib/mentorship-workflow
data-science deep-learning machine-learning python
Last synced: 3 months ago
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This is a repository I give to individuals interested in practical data science and machine learning
- Host: GitHub
- URL: https://github.com/shuyib/mentorship-workflow
- Owner: Shuyib
- License: cc0-1.0
- Created: 2022-07-31T09:36:31.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2022-11-03T11:42:06.000Z (over 3 years ago)
- Last Synced: 2025-07-31T05:58:11.965Z (11 months ago)
- Topics: data-science, deep-learning, machine-learning, python
- Homepage:
- Size: 35.2 KB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# mentorship-workflow
This is a repository I give to individuals interested in practical data science and machine learning. This may eventually be part of the Bioinformatics Hub of Kenya practicals to empower bioinformatician with data science skills that can help them with their work.
Based on conversation with [C.kipkurui](https://github.com/kipkurui) we will breakdown the process into three steps: Foundational skills, Soft skills, Project and writing your life compass.
# Foundational skills
* [] Fundamentals of Data Privacy and Anonymization
* [] Data manipulation in Python, SQL, R & Bash
* [] Data visualization in Python, R & Bash
* [] Machine learning: Supervised Learning, Unsupervised learning, semi-supervised learning and reinforcement learning
* [] Deep learning: Computer vision, Sequence modeling, Generative models (Generative adversarial networks)
* [] Network analysis: Graph metrics, exploring graph databases and creating knowledge graphs.
# Deployment
* [] Docker
* [] Kubernetes
* [] mybinder.org
# Soft skils
* [] Communication on social media
* [] Presentation
* [] Writing a blogpost & Teaching something
# Project
Which project do you want to do? 2 projects max
[] Phylogenetics of 16S rRNA of drug resistant microbes.
[] Siamese CNN or LSTM (Deep learning) with scoring methods to compare sequences of interest.
[] Cell explorer and adaptation of work to bioinformatics.
[] Exploring human 16S rRNA replicating study with investigator methods.
[] Kenya kombucha versus United States(Oakland, California) Kombucha.
[] Epidermic scanner: Use a couple of sources to determine when the next outbreak of certain disease will occur.
[] Resume scanner: Use webscraping and NLP to determine what are skills a candidate is lacking to be on the bleeding edge of the workforce.
# Life compass
This is basically what do you want to do, how can you sustain what you want to do and how can you foster a growth mindset. Don't write it here. Please do that somewhere else safe.
# Goal
Become an effective genomic data scientist who can translate a problem explained by someone into a data science project & deploy your work online.
# Time constraint
todo
# Resources
Please ask your mentor to provide these books and or resources
* [Practical Data Ethics](https://youtube.com/playlist?list=PLtmWHNX-gukKHo6LBrdq82QadvUEwyaJ7)
* [Grokking Machine learning](https://www.manning.com/books/grokking-machine-learning?query=machine%20learning%20%20b)
* [Grokking Deep Learning](https://www.manning.com/books/grokking-deep-learning?query=deep%20learning)
* [Practical Deep Learning for Coders](https://course.fast.ai/)
* [Machine learning bookcamp](https://www.manning.com/books/machine-learning-bookcamp?query=machine%20learning)
* Beat #1 in Kenya on [Rosalind](https://rosalind.info/problems/locations/)
* Try tutorials of interest [Galaxy](https://training.galaxyproject.org/)
* Learn more in this [blog](https://www.notion.so/nyab/Nyabuti-M-c86690dc31a0462abff020498ac557a1): The recommended resources