DataScienceIn60Days

Overview:

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DatasScienceIn60Days is a challenge which is created by me for Myself to learn Datascience within this year(i.e 2018 but its not recommended that you must have start this challenge from now only and finish it before 2018,you can start from anyday but then you have to learn it/practice it consecutive 60 days). But during the planning of this Curriculum i think why to learn alone When i can learn togther with other peoples?? And thats When this idea of making DataScienceIn60Days as challenge arose in mind so other people who are thinking of learning datascience since the starting of the year but due to anyreason they can't learn it ,can start learning it. And i Make this as challenge so we take it seriously and gave our time to learn Datascience daily consecutive 60 days in a row. And also ,The whole curriculum and all the links given below is Completely free.

So if you accept this Challenge then you must have to do these 2 things:

1. Make a Public Pledge to learn or practice DataScience everyday for the next 60 days and post it on any of your favourite social media using #DataScienceIn60Days.

2. Make a record of your work daily by putting what you learn each day on any platform such as github,medium,linkedin etc.

Motivaton:

In Recent Times the need of data Scientist is increasing exponentially.According to glassdoor the number one job in USA is DataScientist.From this you can think How much important is the role of Data Scientist in day to day life.Nowadays in every Industry there is a need of Data Scientist Whether it is technical or non-technical. And other thing is 90% of the data in the world is generated in the past 2 years only and to organize and use that data properly there is a huge demand of Data Scientist.

Course Objective

The main objective of this course is to Learn or Practice Data Science For 60 Consecutive days.

Note: It's Not Recommended to follow this Particular Curriculum only as i am a beginner only so its possible i make any mistake or you dont like my Curriculum, So You can make your own Curriculum also. The main goal behind this challenge is to be consecutive to learn data science for 60 days

Course Length

• 60 Days or 2 Months
• 6 to 7 hours a Day

This Curriculum Includes Following Skills To Become a Data Science:

1. Maths
2. Python Programming
3. Data Preprocessing and Data Visualization
4. Basics of Machine Learning
5. Small Projects(Kaggle)

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1. Maths

(https://www.coursera.org/learn/datasciencemathskills/)

Four Basic Maths Topics Required For Data Science And Machine Learning are:

1. Linear Algebra

(https://www.khanacademy.org/math/linear-algebra)

2. Calculus

(https://www.khanacademy.org/math/multivariable-calculus)

(https://www.youtube.com/playlist?list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr)

(https://www.mathsisfun.com/calculus/)

3. Probability

(https://www.mathsisfun.com/data/probability.html)

(https://www.edx.org/course/introduction-probability-science-mitx-6-041x-2)

(https://courses.edx.org/courses/course-v1:UCSanDiegoX+DSE210x+3T2017/course/)

4. Statistic

(https://www.edx.org/course/foundations-data-analysis-part-1-utaustinx-ut-7-11x-0)

(https://www.edx.org/course/foundations-data-analysis-part-2-utaustinx-ut-7-21x-0)

2. PYTHON PROGRAMMING:

(https://www.youtube.com/watch?v=rfscVS0vtbw&t)

Above Link is of FreeCodeCamp's Youtube Channel. It's a great tutorial which covers everything in one video

3. Data Preprocessing and Data Visualization

3.1 Data Preprocessing

Data Preprocessing can be done by numpy and Pandas Library:

Numpy:

(https://www.youtube.com/watch?v=rvY0MskPps0) (https://www.youtube.com/watch?v=P_3MyPMXN0Y)

Pandas:

(https://www.youtube.com/watch?v=Iqjy9UqKKuo&list=PLQVvvaa0QuDc-3szzjeP6N6b0aDrrKyL-) (https://www.youtube.com/watch?v=yzIMircGU5I&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y)

3.2 Data Visualization:

Data Visualization can be done by Matplotlib Library of Python. It's One of the best Library for Data Visualization in python.You can use anyother of your choice(For eg Seaborn):

(https://www.youtube.com/watch?v=q7Bo_J8x_dw&list=PLQVvvaa0QuDfefDfXb9Yf0la1fPDKluPF)

4.Basics Of Machine Learning:

When its come to Learn Machine Learning then there is a must taken course of Andrew Ng:

(https://www.coursera.org/learn/machine-learning)

5. Small Projects(Kaggle):

First of all see Below 2 videos to get an idea on how to make projects of Data Science and Machine Learning And then Move to Kaggle for Making your own project.Its is Good if you Make Minimum 2-3 Projects on your on own.

Titanic Survivor

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You Can Connect With Me on Below Social Media:

• Linkedin
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