How to Prepare for Data Science Job in 25 Days ?

Prepare for Data Science Job in 25 Days

I have seen people struggling to make their career in Data Science .  It is not really difficult while it is quite easy if you do the preparation strategically  . I have seen people start learning and stop early because they do not have certain goals . This article is completely design for those who want to know How to prepare for Data Science job is 25 Days ?

Steps to prepare for Data Science job –

We will divide this in three chunks . First will cover 10 days and deal with basics . Second will be on machine learning . Last 5 days will be for domain libraries like – NLP , Computer vision etc .

Phase 1 (10 days) –

  1. I am choosing Python for your learning journey . Please visit this complete article for How to cover Python essential for Data Science in 5 Days ? This will guide you to finish or revise the essentials in this path . See ! Please do not miss the order of topics as one may be dependent on another . Day ( 1-5 )

2. Learn the IDE shortcuts and best python programming practices . You may learn and follow PEP-8 programming standard . These python coding standard is commonly adopted across the majority companies in Software Industry with Python language . ( Day 6 )

3. Give two day to learn / revise pandas . This is one of the data analysis library with Python . there are certain operations which are very important in pandas . You should have hands on their syntax like – reading from file , iterating data frame, value based on location , group by operations , merging etc .According to over plan I will give two days to cover these topics . Apart from videos tutorials points is good enough to cover each aspect very quickly here . Day ( 7-8 )

4. Numpy is another library which supports matrix operations in data science . Here you may create multi dimensional array . In order to read you may use tutorial points documentation ( recommended for job preparation ) .You may use our content as well if you need to take a overview only – Day (9-10 )

Numpy Tutorial : A Guide for Beginners (Creation, Conversion ,Indexing )

Phase 2 ( 10 days ) –

5. You should be able to do some sort of data visualization . You need to explore matplotlib for this . I will suggest a source to read edureka blogs . I will recommend you to practice this in 2 days at least .Here hands on knowledge is more important than overview . So please spend some time on drawing graphs etc . Day (11-12)

6. Revise the stats and probability theory also .Day (13-14 )

7.  Go for some machine learning algorithms . Start with classification and regression . Then few algorithms on unsupervised machine learning .  One more and most important advice is – Do not try to cover all possible algorithms in each topic but go to depth of whatever you are reading .  Day ( 14-20 )

Phase 3 ( 5 days ) –

8 . As you know there are few advance field where machine learning and data science is excelling . Most of the industries are working in the same fields . Like NLP , Computer vision, predictive analytics etc . Here you have to master one and now its up to you . Each has its own set of frameworks now you have to practice them .

Day ( 21-25 )


Data Science Learner Team

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Meet Abhishek ( Chief Editor) , a data scientist with major expertise in NLP and Text Analytics. He has worked on various projects involving text data and have been able to achieve great results. He is currently manages, where he and his team share knowledge and help others learn more about data science.
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