Using massive datasets to guide decision is becoming more and more important for modern businesses. with over six times faster growth than other industries, data analytics and data science has become the fastest growing field today. if you are looking for a rewarding career, data science can be a great field. There has been a huge demand for data scientist across the US, EUROPIAN UNION and other countries including India, JAPAN, CHINA and so on.
But most difficult part, if you are beginner, is that from where you can start, starting few days is crucial for anything so starting with data science, following for a life long you need to have proper set of knowledge from where to begin , so here I am listing few open source data sciences course, a 12 week complete study plan which can really help you to take entry in the fields like data science.
But most difficult part, if you are beginner, is that from where you can start, starting few days is crucial for anything so starting with data science, following for a life long you need to have proper set of knowledge from where to begin , so here I am listing few open source data sciences course, a 12 week complete study plan which can really help you to take entry in the fields like data science.
WEEK 1:
For starting with data science you should have good command on python libraries, which are extremely important for data science. python libraries like Numpy, matplotlib and Pandas are most important. So to begin with PYTHON for data science there are many courses available but there is one complete package for data science python. there is a course with the name "Introduction to Python for Data Science" by Microsoft on edx platform which is exceptionally great for beginners in data science, do complete practice of this course for first week and get your hands sharp on these python libraries , do practice as much as you can so that you get clarity on basics programming for data science. here we are also providing a link to that course which you can use to directly go to that course.
WEEK 2:
There are different things that you need to learn while going with this course along with good python programming knowledge you should also have concept clarity about the topics in maths like Statics and Probability. While analysing data in real-world, you need to apply these concepts to filter the data
so along with python you to learn these concepts as well and one best platform to learn these mathematical concepts is Khan Academy. you can learn statics and probability from khan academy.
there are so many concepts on khan academy try to learn basics first so that you can understand the things better while working on data science problems.
my suggestion while doing this part is, focus on the concepts, it might be possible you get bored and distracted while doing this course but believe me if want to learn data science you need to focus on these things. Link to this course is given below :
WEEK 3:
Now after doing these 2-week courses you will get to know what data science is all about and at this point, you need to get your hands on some practical problems and some advancement of data science skills and in this complete week you have to deal with two courses, again first course is by Georgia tech on edx with the name "Introduction to computing for data analysis". and second is you need to practice basic problems on KAGGLE platform, its platform where a data science professional works. Link to this course is given below:
https://www.edx.org/course/computing-in-python-i-fundamentals-and-procedural-programming-0
HERE WE ARE PROVIDING COMPLETE VIDEO FROM WHERE YOU CAN GET MORE INFORMATION ABOUT 3 MONTHS DATA SCIENCE COURSE:
We Will telling you more about it in other parts of this Article, till then stay tuned and if you like our work please do follow.
HERE WE ARE PROVIDING COMPLETE VIDEO FROM WHERE YOU CAN GET MORE INFORMATION ABOUT 3 MONTHS DATA SCIENCE COURSE:
We Will telling you more about it in other parts of this Article, till then stay tuned and if you like our work please do follow.
Very Nice Brother
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