Knowledge studying assets on the backside!
I’ve determined to upskill as a lot as potential in my final yr in faculty and to try this, I’m studying in public to carry myself accountable + share my learnings. That is what I name my Growth & Accountability project, and to assist information my studying I’ve 9 Verticals I’m making an attempt to pursue.
One of many 9 Verticals I’m serious about is: Knowledge (known as AI & ML on my weblog). This text is my define for the way I’m making an attempt to be taught knowledge from the analysis I’ve completed over the previous few weeks. It’ll cowl: the place I’m at, what I’ve researched, and my total technique for studying knowledge + some suggestions for assets (I’ve a reasonably complete record of programs, which you’ll see beneath).
Let me know what you suppose, and provides me extra suggestions!
The place am I now?
I feel that every one issues thought of, I’m in a reasonably good place to start. Previously three years at college, I’ve managed to take a couple of coding, statistics, and calculus courses. So I’ve some coding expertise + the fundamental foundations to begin from. I’m additionally fairly good with Excel, and so I hope I’ll have the ability to leverage that to get a bit bit forward in my course of.
What are my objectives?
By the top of this, I would like to have the ability to do a couple of issues:
1. Confidently analyze any knowledge set
2. Visualise knowledge units in ways in which look skilled and are helpful
3. Develop my knowledge storytelling abilities
4. Develop fashions which are capable of predict outcomes and recommend suggestions
5. A fundamental understanding of the best way to arrange knowledge infrastructure for corporations
I additionally want to have developed a portfolio of labor to spotlight my efforts and have gotten 80% of the way in which there by the center of September (2.5 months) + do all of it totally free. Seemingly this scope will broaden a bit with time, however these are presently the issues I’m aiming to be taught.
What are the precise abilities I must be taught?
- Knowledge evaluation (Python, R, Pandas, Numpy, SQL
- Knowledge visualization( Tableau & Graph making + different instruments)
- Knowledge storytelling (with apply)
- Knowledge fashions & prediction (Scikit be taught, TensorFlow, PyTorch)
- Different abilities (Constructing APIs, Kubernetes, Docker)
My method?
Venture Targeted. I would like my method to be project-focused for a couple of causes: so I’m capable of look again at what I’ve achieved, have the ability to showcase my work, and have precise hands-on studying. I’d additionally wish to keep away from writing any of my code utilizing AI, solely utilizing AI for questions — I need to really be taught what’s happening beneath the hood.
How will I be taught?
Regardless of my focus being on initiatives, I do want to begin studying someplace, and I can most successfully do that through on-line programs. Whereas I’m not fairly ranging from nothing, I nonetheless need to develop a grasp of the sphere and actually perceive what it’s I must be taught to develop the abilities I’m in search of. In doing so, I additionally need to begin by taking free programs which are shorter so I’m capable of adapt my technique as I be taught.
Particularly, these are the programs I need to begin off with:
From there, I ought to have a greater understanding of my ability, and solely after that may I begin looking at among the programs I’ve discovered beneath.
How will I apply?
Subsequent Steps
Hopefully, this needs to be a great begin. I nonetheless have loads to determine relating to my total technique, however that is how I’m planning on studying Knowledge Science in 2025. Please let me know what assets have been helpful for you, in addition to any suggestions & methods you might need for this undertaking.
Take a look at my linktree to be taught extra about my accountability undertaking: https://linktr.ee/untitledaccountability
As promised, right here’s my lengthy record of programs in addition to some particulars about them, take pleasure in!
Khan Academy (free)
Coursera
- AI for everybody — Andrew Ng (6 Hours complete)
- IBM AI Developer Skilled Certificates — IBM (4 hrs weekly, 6 months), Studying software program engineering, Flask, python, knowledge science, and so on
- IBM Knowledge Science Skilled Certificates — IBM (10 hrs weekly, 4 months), Python, Knowledge science, knowledge visualization, databases, machine studying
- Deep Studying Specialisation — Andrew Ng (10 hrs weekly, 3 months), AI Fashions — (CNNs, Deep Neural Networks, Sequence Fashions)
- Machine Studying Specialization — UWash (10 hrs weekly, 2 months), Machine Studying, Regression, Classification, Clustering, Retrieval
- Python for everybody — UMich (10 hrs weekly, 2 months), Primary Python + Knowledge constructions, databases, accessing internet knowledge, visualisation
- Machine Studying Specialisation — Andrew Ng (10 hrs weekly, 2 months), Machine studying, supervised, unsupervised, reinforcement, classifiers, regression
- Deeplearning.ai Knowledge Engineering Skilled Certificates (10 hrs weekly, 3 months) Knowledge Sources, pipelines, storage, ingestion, modeling, serving
- Deeplearning.ai Knowledge Analytics Skilled Certificates (5 hrs weekly, 4 months), Basis, Utilized statistics, Python, I/O, preprocessing, storytelling
Udacity (Paid)
- Programming for Knowledge Science with Python — 53 hours SQL, Python, Tableau
- Intro to TensorFlow for Deep Studying, CNNs, Time sequence forecasting, NLP
- HarvardX: CS50’s Introduction to Synthetic Intelligence with Python
Google Builders (free)
- Machine Studying Course, Lots of ML subjects coated
Kaggle (free)
- Pandas 4 hrs
- Knowledge Visualisation 4 hrs
- Intro to SQL 3 hrs
- Superior SQL 4 hrs
EDX (Harvard EDU) (free with no certificates + no grading)
- Introduction to Knowledge Science with Python — 3–4 hrs weekly, 8 weeks
- Knowledge Science: Visualization- 1–2 hrs weekly, 8 weeks
Udemy (free with no certificates)
- Introduction to Knowledge Science utilizing Python (Module 1/3) — 2.5 hrs, Knowledge Science Overview
- Knowledge Science, Machine Studying, Knowledge Evaluation, Python & R— 8 hrs, Knowledge visualization, evaluation, loading
Different
Thanks for studying!
