Can you get a job in data science and machine learning without a college degree?

🧵👇

Short Answer: Yes.

Long Answer, keep reading 👇

(Advice from industry experts who I talked to.)
Companies are looking for people who add value.
In order to add value, you'll need skills. Simple as that.

Get the skills to provide value and you'll get the job.
In the age of the internet where everything is pretty much free, why do college degrees matter?

A college degree makes it easier to get the skills to get a job in machine learning or data science.
College degrees also help you make many useful connections and provides many opportunities in the form of internships and whatnot.

College degrees have their own place
However that does not mean that you cannot get into these fields without a degree, it'll just take more work.
For machine learning and data science you mainly need 3 skills:

- The theoretical part which mainly includes math
- The practical part which includes programming skills
- An understanding of the industry in which one is applying machine learning and data science
Most people will probably stop here because of the math.

Math is important, but not when you are starting out. You can learn math as and when you need it, programming is actually the more important part.
Start by having strong fundamentals in programming.
This is more important than you think it is.
Python, R and Julia are some of the options out there.
Python is the most recommended for several reasons.
Next, work on a few Kaggle challenges by taking the help of submissions of other users, the docs and the internet.

While you are making these models, try to research a bit more about what's going on under the hood.
If you're making a neural network, try researching about the some of the activation functions you have used in the model.
This was just one approach to learning the skills needed for machine learning and data science. Do what works for you, just get the job done.
And of course, this isn't going to be a very easy process.

It could take more than a year before you could get ready for applying to jobs.

That doesn't mean it can't be done.

More from Pratham Prasoon

More from Machine learning

10 PYTHON 🐍 libraries for machine learning.

Retweets are appreciated.
[ Thread ]


1. NumPy (Numerical Python)

- The most powerful feature of NumPy is the n-dimensional array.

- It contains basic linear algebra functions, Fourier transforms, and tools for integration with other low-level languages.

Ref:
https://t.co/XY13ILXwSN


2. SciPy (Scientific Python)

- SciPy is built on NumPy.

- It is one of the most useful libraries for a variety of high-level science and engineering modules like discrete Fourier transform, Linear Algebra, Optimization, and Sparse matrices.

Ref: https://t.co/ALTFqM2VUo


3. Matplotlib

- Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.

- You can also use Latex commands to add math to your plot.

- Matplotlib makes hard things possible.

Ref: https://t.co/zodOo2WzGx


4. Pandas

- Pandas is for structured data operations and manipulations.

- It is extensively used for data munging and preparation.

- Pandas were added relatively recently to Python and have been instrumental in boosting Python’s usage.

Ref: https://t.co/IFzikVHht4
10 machine learning YouTube videos.

On libraries, algorithms, and tools.

(If you want to start with machine learning, having a comprehensive set of hands-on tutorials you can always refer to is fundamental.)

🧵👇

1⃣ Notebooks are a fantastic way to code, experiment, and communicate your results.

Take a look at @CoreyMSchafer's fantastic 30-minute tutorial on Jupyter Notebooks.

https://t.co/HqE9yt8TkB


2⃣ The Pandas library is the gold-standard to manipulate structured data.

Check out @joejamesusa's "Pandas Tutorial. Intro to DataFrames."

https://t.co/aOLh0dcGF5


3⃣ Data visualization is key for anyone practicing machine learning.

Check out @blondiebytes's "Learn Matplotlib in 6 minutes" tutorial.

https://t.co/QxjsODI1HB


4⃣ Another trendy data visualization library is Seaborn.

@NewThinkTank put together "Seaborn Tutorial 2020," which I highly recommend.

https://t.co/eAU5NBucbm

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शमशान में जब महर्षि दधीचि के मांसपिंड का दाह संस्कार हो रहा था तो उनकी पत्नी अपने पति का वियोग सहन नहीं कर पायी और पास में ही स्थित विशाल पीपल वृक्ष के कोटर में अपने तीन वर्ष के बालक को रख के स्वयं चिता पे बैठ कर सती हो गयी ।इस प्रकार ऋषी दधीचि और उनकी पत्नी की मुक्ति हो गयी।


परन्तु पीपल के कोटर में रखा बालक भूख प्यास से तड़पने लगा। जब कुछ नहीं मिला तो वो कोटर में पड़े पीपल के गोदों (फल) को खाकर बड़ा होने लगा। कालान्तर में पीपल के फलों और पत्तों को खाकर बालक का जीवन किसी प्रकार सुरक्षित रहा।

एक दिन देवर्षि नारद वहां से गुजर रहे थे ।नारद ने पीपल के कोटर में बालक को देख कर उसका परिचय मांगा -
नारद बोले - बालक तुम कौन हो?
बालक - यही तो मैं भी जानना चहता हूँ ।
नारद - तुम्हारे जनक कौन हैं?
बालक - यही तो मैं भी जानना चाहता हूँ ।

तब नारद ने आँखें बन्द कर ध्यान लगाया ।


तत्पश्चात आश्चर्यचकित हो कर बालक को बताया कि 'हे बालक! तुम महान दानी महर्षि दधीचि के पुत्र हो । तुम्हारे पिता की अस्थियों का वज्रास्त्र बनाकर ही देवताओं ने असुरों पर विजय पायी थी।तुम्हारे पिता की मृत्यु मात्र 31 वर्ष की वय में ही हो गयी थी'।

बालक - मेरे पिता की अकाल मृत्यु का क्या कारण था?
नारद - तुम्हारे पिता पर शनिदेव की महादशा थी।
बालक - मेरे उपर आयी विपत्ति का कारण क्या था?
नारद - शनिदेव की महादशा।
इतना बताकर देवर्षि नारद ने पीपल के पत्तों और गोदों को खाकर बड़े हुए उस बालक का नाम पिप्पलाद रखा और उसे दीक्षित किया।