Tue, 12 Feb, 2019 @ 02:51:07

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"raheem nasirudeen Feb 11 Data is really every where The amount of data we produce every day is truly mind-boggling. There are 2.5 quintillion bytes of data created each day at our current pace, but that pace is only accelerating with the growth of the Internet of Things (IoT). Google, Amazon, Facebook etc generate data a lot. Just everywhere all over the world Artificial Intelligence is now becoming the hype. You are just in a tech community or meet-up you ear people talking about Data Science, Machine Learning and AI. You feel like whao this career is going to make me rich soon🤑 after googling more about it seeing many Forbes list naming it as one the most fast growing job and highest paying job in the world. Newbie: AI as show many branches link https://www.google.com/amp/s/blog.adext.com/en/artificial-intelligence-technologies-2019%3fhs_amp=true. 14 month little experience as Data scientists from Statistics background is very interesting and Challenging. You feel like I have to get started in data science world. Bravo💪 When starting data science you get into a community you get to know either Python or R Language as one the powerful tools to get started with and you start learning it to be a good data scientists enthusiasts 😀 and you start following someone Courses online then you see “learning Data science in a month on your timeline” you feel like after this course you become AI guru🙄 then you start it and finish it to become AI guru👏. Note: Did you even take the right course to get you introduce to what Data science really means, just because inside the course they tell you different ways to analyze data and every time your journey start with. Import pandas as pd Import numpy as np You get introduced to machine Learning which you learn about Supervised, Unsupervised and Reinforcements Learning. Link: https://www.dummies.com/programming/big-data/data-science/3-types-machine-learning/ You like whao am now a guru in Data scientists in your mind. Data science, Machine Learning and Artificial Intelligence really takes a long way to go. Like 3 first course you actually did comes with a very neat data mostly use Classification Algorithm you see 97% all time you say this Good. 1. Make sure you get the right data for question you are asking. 2. Understand the data/ Business understanding 3. Data preprocessing a very interesting and brainstorming stage. 4. Building of models using various algorithm. 5. Evaluate to check if you are right if not take from 1step again. 6.Deploy your model. Data scientists spend 80% of their time in the processing stage. I’m just a lazy writer😧😧 to mention few there are many ways to get started. 1. Learn either Python or R 2. Take datcamp.com course introduction to Data Science Python or R edition 3. Learn on udemy.com Python for data science bootcamp. 4. Take Andrews Ng course. 5. Read as many textbook on Artificial Intelligence, Machine Learning and Data scientists. 6. Read as many blog you can. 7. Lot more you take time to learn about SQL, Tableau or Power BI. Just a little for now in my next article I will get to introduce Practical and theoretical aspect In day to day data science task. Please Read more on many articles in data science world. By: Reheem nasirudeen

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