https://github.com/harshstats/practical-data-science-specialization
https://github.com/harshstats/practical-data-science-specialization
Last synced: 30 days ago
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- Host: GitHub
- URL: https://github.com/harshstats/practical-data-science-specialization
- Owner: HarshStats
- Created: 2023-11-06T04:29:35.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-04T15:11:42.000Z (almost 2 years ago)
- Last Synced: 2025-03-18T16:54:33.488Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 3.18 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# My Journey Through Practical Data Science on AWS
Welcome to my repository, where I chronicled my adventures in the Coursera course, Practical Data Science on AWS. This course was an incredible opportunity for me to dive deep into data science and machine learning, leveraging the power of AWS Cloud services, especially Amazon SageMaker.
## Course Reflections
Throughout this course, I engaged with three pivotal modules:
1. I analyzed datasets and trained ML models using AutoML.
2. I built, trained, and deployed ML pipelines using BERT.
3. I optimized ML models and deployed human-in-the-loop pipelines.
Each step of the way, I focused on practical AWS applications, tackling real-world data science challenges, from comprehensive data analysis to deploying scalable machine learning models.
## Starting Point
Initially, I ensured I had an AWS account and cloned this repository to access all the course materials, including notebooks, datasets, and instructions.
## Prerequisites I Met
I brushed up on my Python and basic data science knowledge.
I prepared my AWS account for the hands-on exercises.
Resources I Used
I followed the course materials and instructions provided within each module's directory.
For extra support, I frequently consulted the AWS documentation and participated in Coursera forums.
Acknowledgments
I'm grateful to Coursera and AWS for offering the resources and platform that guided me through this specialization.
Here's to learning and growing!