Data Science Tutorial | Data Science for Beginners | Data Science with Python Tutorial | Simplilearn

///Data Science Tutorial | Data Science for Beginners | Data Science with Python Tutorial | Simplilearn

Data Science Tutorial | Data Science for Beginners | Data Science with Python Tutorial | Simplilearn

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This Data Science Tutorial will help you understand what is Data Science, who is a Data Scientist, what does a Data Scientist do and also how Python is used for Data Science. Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining. This Data Science tutorial will help you establish your skills at analytical techniques using Python. With this Data Science video, you’ll learn the essential concepts of Data Science with Python programming and also understand how data acquisition, data preparation, data mining, model building & testing, data visualization is done. This Data Science tutorial is ideal for beginners who aspire to become a Data Scientist.

This Data Science tutorial will cover the following topics:

1. What is Data Science? ( 00:43 )
2. Who is a Data Scientist? ( 02:02 )
3. What does a Data Scientist do? ( 02:25 )

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#DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning

This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.

Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. A data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.

You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to:

1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics.
Install the required Python environment and other auxiliary tools and libraries
2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions
3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions
Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO and Weave
4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package
5. Gain expertise in machine learning using the Scikit-Learn package

The Data Science with python is recommended for:
1. Analytics professionals who want to work with Python
2. Software professionals looking to get into the field of analytics
3. IT professionals interested in pursuing a career in analytics
4. Graduates looking to build a career in analytics and data science
5. Experienced professionals who would like to harness data science in their fields

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By |2019-08-09T21:55:55+00:00August 9th, 2019|Python Video Tutorials|26 Comments

26 Comments

  1. Simplilearn August 9, 2019 at 9:55 pm - Reply

    Do you have any questions on this topic? Please share your feedback in the comment section below and we'll have our experts answer it for you. Also, if you would like to have the dataset for implementing the use case shown in the video, please comment below and we will get back to you.
    Thanks for watching the video. Cheers!

  2. Madhuri Maharana August 9, 2019 at 9:55 pm - Reply

    Hello sir , i'm getting 2 errors here:
    1. ModuleNotFoundError: No module named 'statsmodels'
    2.
    ValueError: labels ['columns_2017'] not contained in axis
    please lemme know what to do next?

  3. David Kennedy August 9, 2019 at 9:55 pm - Reply

    Very well presented. I want to know more…

  4. Jaya Raju August 9, 2019 at 9:55 pm - Reply

    Is these videos are enough for learn data science?

  5. Alamgeer August 9, 2019 at 9:55 pm - Reply

    please send all of your slide at alamgeer0949@gmail.com from start of viedo to last viedo.

  6. PAVITHRA VASU August 9, 2019 at 9:55 pm - Reply

    Hello the tutorial was useful. But can you explain me of how codes are done and how to present them to the end user. pavithravasu999@gmail.com

  7. Sageer Hossain August 9, 2019 at 9:55 pm - Reply

    Can u please provide the dataset on this id sageergreen@gmail.com

  8. Kemuel Sabula August 9, 2019 at 9:55 pm - Reply

    Hey could you please send the data set used in the tutorials and the python programs . My email is kemuelsabula@gmail.com

  9. Ms Prakruthi August 9, 2019 at 9:55 pm - Reply

    Very impressive…PPT are very easy to understand, the presentation is very cool.

  10. prajakta sonawane August 9, 2019 at 9:55 pm - Reply

    Good Explanation. please, can you share the practical videos of data science.

  11. amruth bellala August 9, 2019 at 9:55 pm - Reply

    Hi Simplilearn, Can u send me the data set used in this tutorial to this id aravindan.amruth@gmail.com

  12. annexin August 9, 2019 at 9:55 pm - Reply

    There is only ONE THING I WANT TO KNOW: WHAT IS THE NAME OF THE PRESENTER? HE IS ABSOLUTE STELLAR!

  13. Venkat Dongara August 9, 2019 at 9:55 pm - Reply

    what are hadoop tools needed to perform data science tasks?

  14. Venkat Dongara August 9, 2019 at 9:55 pm - Reply

    Good one for beginners

  15. sagara ks August 9, 2019 at 9:55 pm - Reply

    High Programming knowledge is required for this job?

  16. Praveen kumar August 9, 2019 at 9:55 pm - Reply

    Good

  17. saurabh bhujbal August 9, 2019 at 9:55 pm - Reply

    Sir plz speak in hindi

  18. shubham kumar August 9, 2019 at 9:55 pm - Reply

    deep understanding about data science .love it .

  19. Arun Kumar Agarwal August 9, 2019 at 9:55 pm - Reply

    tutorial is cool. India is the happiest nation on this planet and i belong from india the mother of all civilisation.

  20. Sathya Rao August 9, 2019 at 9:55 pm - Reply

    Thanks for detailed video illustrated with examples. However, I being in Industry for 30+ years, suggest that, please list prerequisites like knowledge of concepts like Correlation, Coefficient, Mean etc and what they mean when we compare the Parameters and cofficients. If possible also include link to understand those concepts.
    Thanks,
    Sathyanarayana Rao Ranya
    94489 56408

  21. Timo Kivumbi August 9, 2019 at 9:55 pm - Reply

    Thanks for the lesson, can you please share the data set used?

  22. Solly Sebela August 9, 2019 at 9:55 pm - Reply

    Hi brilliant stuff!! can you please share dataset to solly9sebela@gmail.com

  23. NJOKU MAC ANTHONY August 9, 2019 at 9:55 pm - Reply

    sir your videos are great ,but they have much size in megabyte, i wish u can work on that. thanks

  24. rybltbt August 9, 2019 at 9:55 pm - Reply

    Hello can you share the python program for this you tube? I want to play around the table of happiness using python

  25. Mohan Krishna V August 9, 2019 at 9:55 pm - Reply

    can we call categorical also as discrete values?

  26. Mohan Krishna V August 9, 2019 at 9:55 pm - Reply

    at 9:00 you said to replace blank values by mean.Is it not a good idea to delete those rows with null or in compatible data.

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