Unveil DataScience/AIML Myths

Hello Folks ! Thinking of moving on to Data science career just because of lucrative Salary ? Hold On. Have a glance on this article, introspect and then decide.

I am the future

Common doubts and myths about Datascience :-

1. Are Data scientist, Data Analyst, Data Engineer same?
   No. They aren’t.

Data Engineer :- Focus on data collection and storage. Build Data pipelines ans storage solutions. Information Architect. Maintain Data Access.
Skills:- SQL — To store and organize data.java, Scala,Hadoop, Python-to process data.Shell Command to automate and run task.

Data Analyst :- Focus on data Preparation, Exploration and visualistion for reports /dashboards to summarize data. Data cleaning.
Skills :- SQL, Excel, and Power BI, SSAS, Tableau , Python for Data Visualisation.

Data Scientist :- Data Preparation -Data cleaning, Feature Engineering, Feature scaling.
EDA — Exploration using charts, Visualisation using scikit package graphs
Experiment and Prediction -using ML algorithm.
Skills :- Statistics, Tableau, Python/R, AZURE-ML, AWS-ML.

ML Engineer :- More specific to prediction using algos and Deep Learning for AI. — Image processing, NLP.

2. Is Data Scientist a highly paid Job?
There is a buzz and hype at present and indeed it is highly paid job for right candidate but as the market grows and more people flush in , situation may not be the same.

3. Do we need prior programming knowledge ?
Not exactly. Although you need analytical skills, functional approach.

4. Do we need heavy Mathematics ?
School level Probability, statistics, Linear Algebra and Calculus is enough.

5. Python OR R?
Each language comes with it’s own Pro-cons. However Python has more advanced community support and ML libraries. R is used mainly in Visualisation.

6. Should I join course or not ?
If you have self-learning ability then there are enough material available online on youtube. Otherwise you can join Online/Offline course like
Great-learning, Edureka, Coursera, Upgrad, Datacamp, Simplilearn.

Source:- https://analyticsindiamag.com/

7. Will Data-science profile suit me ?
If you like to play with Data, have analytical approach and love Maths then you can excel. And if you wanna transition to some other career option like this just because you are underpaid, stuck in some boring job or not liking Hard core programming like Java, .Net then BEWARE.. you may repent later.

So, What is Data Science:- It is a combo of Maths, data analysis and machine learning algorithm to extract Knowledge/info based on prediction from structured/unstructured data. Further ML and Deep ML is used in AI. the scope and impact of data science will continue to expand enormously in coming decades as scientific data and data about science itself become ubiquitously available. Start with below books :-

1. Intoduction to machine Learning with Python — O’Reilly
2. Python Machine Learning — Packt- Sebastian Raschka
3. Hands-On ML with Scikit-Learn & TensorFlow — O’Reilly
4. Applied Artificial Intelligence — Handbook.

All the Best ! Let’s Start.

Do checkout my other blogs:-

✔Cross Validation Machine Learning: K-Fold

✔Model Performance -Hyper-parameter Tuning

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