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Data Science and Machine Learning with Python and Libraries


Data Science and Machine Learning with Python and Libraries


Data Science and Machine Learning with Python and Libraries Learn Data Science and Machine Learning with Python and Libraries such as Numpy, Matplotlib, Pandas and much more!

What you'll learn

  • Data Science with Python
  • Using Python Libraries for Data Science
  • Data Analysis
  • Python Libraries such as Numpy, Matplotlib, Pandas
  • Visualizing Data
  • Linear Algebra
  • Statistics
  • Probability
  • Hypothesis and Inference
  • Gradient Descent
  • Machine Learning
  • k-Nearest Neighbors
  • Naive Bayes
  • Simple Linear Regression
  • Multiple Regression
  • Logistic Regression
  • And Much More!


  • A little bit of Python understanding will be good (not necessary)



As the world is progressing in science and technology, there is an enormous increase in the need for advanced tools to store information and mine data that is being produced indefinitely. And the key to this problem is data science. Data science is a field of study that develops scientific and systematic methods to record, process and analyze data to withdraw significant and useful information that can be both structured and unstructured. Unstructured data is the one that is generated by mobile devices and websites while structured data is an organized data which is mostly generated by the users e.g. emails, chats, telephone calls etc. Data science uses scientific methods and algorithms to extract knowledge. Industries require the use of this field immensely and the industrialists now realize the value of data science and the benefits it can provide to the business, thus, it has become very popular currently.

The need for data science

An immediate question that rises in the mind after hearing about data science is why is there a need to dig into depths for such a tool? So, it’s important to understand that previously the data produced used to be structured and thus it was somehow easy to extract the meaningful information and process it. However, contemporarily the data that is being produced is mostly unstructured as there are multiple sources of its generation such as multimedia files, logs, documents etc. and data science provides aid in turning raw data into consequential one.

Human brains possess the intelligence to perceive things as they are i.e. processing the information that we see and store it. It is just a power that we humans have and because we are doing it constantly without any deliberate effort, it is trivial to us. However, parallel to this brilliant power that we hold, it is also to have a clear understanding of the fact that it is limited. Human brain is also prone to forgetting, and impeding memory, perceptions and predictions. Here, the computer’s prowess proves to be helpful. With the advance improvement in technology, we are now able to leave our locations through our smartphones for example uber that makes our traveling so much convenient, our movements can be tracked easily, our online behaviors and patterns of search are constantly being recorded through our acceptance of cookies, the steps we take during a day can be tracked by the help of some specific apps, even our health can be tracked. All of this is possible due to the invention of technology, softwares and the ability to record and process information adequately. Our information is being stored and without us even noticing. This tracking ability is not only applicable on the people sitting at home, but government agencies, stock markets, civil officers, intelligence agencies, business owners are all the concerned parties and is useful for each one of the occupations. Data science is used in providing systematic methods to give useful insights from the enormous data that is being generated. Therefore, data science is indeed important.

Other than the general importance, data science is extremely beneficial to the business in numerous ways:

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