Data Science E-Learning
Data science is a multidisciplinary field that combines statistics, computer science, and domain knowledge methods to extract meaningful insights and wisdom from data. It involves collecting, analyzing, and interpreting large amounts of structured and unstructured data to make informed decisions, predict future trends, and solve complex problems.
Gathering data from various sources, such as databases, sensors, or web scraping.
Preprocessing data to remove errors, inconsistencies, or missing values.
Applying statistical techniques and algorithms to uncover patterns, relationships, and trends.
Developing models that can learn from data to make predictions or classifications.
Presenting the data and findings in graphical formats to make the results easier to understand.
Concluding the analysis and applying them to solve real-world problems.
Data science is used in many industries, such as finance, healthcare, marketing, and technology, to improve operations, forecast trends, and drive innovation.
Data science is used to study data in the following ways:
- Descriptive Analysis
- Diagnostic Analysis
- Predictive Analysis
- Prescriptive Analysis
Python is a programming language widely used by Data Scientists. It has some libraries with large collections of mathematical functions and analytical tools. In this tutorial, we will use the following libraries:
This library is used for structured data operations, like importing CSV files, creating data frames, and data preparation
It is a mathematical library with a powerful N-dimensional array object, linear algebra, the Fourier transform, and more.
This library is used to visualize data.
This library has linear algebra modules