Thepersonalmsds
The Personal MS(DS) is an initiative to customize the Data Science Masters roadmap according to one's interests hence providing complete autonomy to the learner. The intuition behind #thepersonalmsds is to upgrade skills without formally enrolling into a Master's program at a University
Install / Use
/learn @mhjhamza/ThepersonalmsdsREADME
Welcome to The Personal MSDS!
The Personal MS(DS) is an initiative to customize the Data Science Masters roadmap according to one's interests hence providing complete autonomy to the learner. The intuition behind #thepersonalmsds is to upgrade skills without formally enrolling into a Master's program at a University. ThePersonalMSDS (beta) is an amalgam of handpicked content taught at different Pakistan-based and International universities based on the student’s feedback. Majority of the content mentioned in #thepersonalmsds can be easily found online. Most of the topics revolve around Mathematics, Statistics, Machine Learning, Deep Learning, Data Science, AWS Cloud Services, and Big Data. Each mini-semester revolves around a particular domain; each mini-semester contains a hand-full of languages, frameworks and libraries.

Links that you should keep visiting
| Important Links | Link | | -- | -- | | Keep an eye on my progress using this TIL file (2021) | Todayilearned | Keep an eye on my progress using this TIL file (2019) | Todayilearned | My last-year ML challenge can be found here | #100DaysOfMLCode | Tedtalks - Making Sense of too much data | Click here! |
List of Participants
Want to take the challenge?
Getting Started with thepersonalMSDS
Course wise content and self-studying material
This contain links to all the relevant books, courses, videos and specializations
| Course Title | Link | | -- | -- | | Personal Development | Click here! | Statistics | Click here! | Mathematics | Click here!| | Big Data | Click here! | Mathematics | Click here!| | Machine Learning | Click here!| | Deep Learning | Click here!| | Data Science | Click here! | AWS Machine Learning (Speciality) | Click here! | | AWS Big Data (Speciality) | Click here! |
University wise MS(DS) Roadmaps (National/International)
| University | MSDS Roadmap | | -- | -- | | ITU - Information Technology University | ITU Lahore MS(DS) Roadmap | FAST Lahore | FAST Lahore MS(DS) Roadmap | Please contribute more roadmaps | Thanks!
Note: Feel free to actively contribute in the MS roadmap; If you come across a decent learning material [either paid or free] create a pull request. Contributors will be given credits by referring to their Linkedin / Github profile.
How can I contribute?
- Contribute by sharing your universities MS(DS) Roadmap.
- Contribute by sharing any online course or specialization you enjoyed!
- Contribute by sharing relevant book(s) for a particular course.
- Contribute by sharing Udacity Nano-Degree's code/content.
- Contribute by sharing TEDtalks on Data Science in the relevant directory.
MSDS Roadmap
The tentative roadmap covers four mini-semesters in ~4-6 months:
- Personal Development
- Mathematics
- Statistics
- Big Data
- Machine Learning
- Deep Learning
- Data Science
- Final Kaggle/Project
Milestones
- AWS Machine Learning (Speciality)
- AWS Big Data (Speciality)
About me
Muhammad Hamza Javed is an AWS Certified Solutions Architect - Associate, an AWS Certified Developer, a Packt Author, and a Data Science enthusiast primarily working on Machine Learning, Deep Learning, and Computer Vision. He possesses a Bachelor's Degree in Computer Science from GC University and forty-five (45) certificates in Data Science, Machine Learning, Deep Learning, and Big Data from AWS, Coursera and LinkedIn.
Recent Accomplishments as of 2019:
- AWS Certified Solutions Architect - Associate
- AWS Certified Developer - Associate
- Packt Author - Computer Vision Course
- Packt Author - Geting Started with Tensorflow 2.0 for Deep Learning
- 100DaysOfMLCode
Contact: Linkedin | Kaggle | Facebook | Packt
Metadata
Content-Types: Books, Coursera, Udemy, Packt, Youtube, Articles, and Tedtalk Tags: MSDS, Masters, DataScience, MachineLearning, DeepLearning, AWS, AWSCloudServices, BigData
Security Score
Audited on May 14, 2023
