DATA SCIENCE from Scratch!

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#20 WEEKS of Data Science.

#Week 1 — PART 1

If you are just getting started with Data Science or looking forward to brush up your skills, Hurray! you have landed up in the right place.

Image credits Dribbble

What is Data Science?

Wiki’s Recipe:

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data.

Our Recipe:

  1. Collecting the data
  2. Data acquisition
  3. Data cleaning
  4. Exploratory Data Analysis
  5. Data modeling
  6. Data Visualization
  7. Deployment, and Maintenance.

All in one, combined is called Data Science and the best is yet to come.

Will be explained soon -Stay tuned [*upcoming weeks]

A Noob to the field may be stunned by looking at all the fancy TERMINOLOGIES.

Don’t Panic! Follow M&M's Path towards Data Science for weekly resources and articles towards Success.

Data Science is a combination of ML, Math and Statistics, Programming, and Business / Domain Knowledge.

This can be well picturized by the following image, which is seen in most of the seminars and videos related to data science.

The ultimate Venn diagram from MEDIUM Article

We will help you decode the most efficient and fastest way of enjoying the journey towards Data Science by being an imaginary one!

THE MAGICAL PATH TOWARDS DATA SCIENCE:

Your Data Science path is your own!

Remember that everyone has to go with their flow and face their hassles to be a better version of themselves.

Why would you want to be on someone else’s journey when you can surely create one for yourself?

Accepted that, other peers’ Data science journey might be more resourceful! Of course, You can take insights from them and create your own PATH!

Gif Credits @ Dribble.com

Your investment of time, smart work, and passion towards your own professional path can make it a little extravaganzaaaaaa than you think!

Focus on fundamentals as it is the building block for your success!

Here is a secret !! woo-hooo Don’t tell it to anyone(whispering..!)

Try using the Best learning technique called the Feynman technique!

Image Credits Quora

Stepping stones in achieving Your path!

Image credit @Pintetrest
  1. Work on your mindset to give yourself a dedicated time (2- 3 hours) / day to work towards your professional goal.
  2. Goal setting is easy. But you want to achieve it right?- Avoid distractions.
  3. Now it takes a little more effort than usual, yup it is difficult as a toddler but you can work on it to make it easier.
  4. Have in mind that, We are all in this together ‘sailing on the same boat in the wide sea’ but decide who is the captain?
  5. Don’t PROCRASTINATE, don’t overthink, and just do it!
  6. Grasp Failure because failure is just a new opportunity to do it once again but a little better and also Learn to Love Debugging.
  7. What language should I learn?” Still in dilemma? Choose one and move on. (We prefer Python).
  8. At last “Begin With the End in Mind” — Observe the quote keenly to understand its view. (Observing is a key to success in any field!).

Here is the Data scientist the @DataProfessor himself who created this wonderful picturization of Data Science in one image!

Image credit @DataProfessor Chanin Nantasenamat, DataScience Professor

Don’t get confused! Feel free to post your Feedback or questionnaire as comments and we will do our best to communicate the right answers to you!

19th century- “Believe in God”

21 st century- “Believe in Data”

“The world is one Big Data problem”

-Andrew McAfee (principal research scientist at MIT)

We @(M&M)spiced it up as!

“Whoever solves it, gets paid for it!”

Conclusion

Data science as a professional path is a great option that is interesting, challenging as well as rewarding.

The demand for data scientists is just going to explode, HaHa :) no it has already exploded now!

If you liked this article, please share with your friends. They will thank you for it!

— — — — — — — — — — — — — — — — — — — — — — — — — — — — — -Happy Learning😊

#Thanks for insights from Medium Towardsdatascience

This article was originally written by two ambitious Budding Data Scientist(s).

STAY TUNED FOR next weeeek !

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