In this topic, students will learn the basic software required for data science. Also, they will learn to install and use Jupyter Notebook, will know more about the shortcuts to use the Jupyter Notebook.
Python for Data Science
This is a separate module that consists of the basic building blocks of Python programming. In this module, students will have a deeper look at the concepts of Python like data types, variables and constants, input-output methods, control structures, and data structures of Python programming.
Variables and Constants
Handling Input and Output
Introduction to Functions
Sequential Control Structure
Decision Control Structure
Loop Control Structure
Data Structures in Python
User Defined Subprograms
In this module, students will learn to handle the database using SQL commands. Students will learn more about relational databases.
Types of Databases00:00:00
The primary focus will be on MongoDB. In which students will get to know about the operators used in this database and they will perform CRUD operations.
Relations between Collections00:00:00
NumPy is a popular python library used for working with arrays, linear algebra, etc. Students will learn in-depth about the usage of this library.
nd Array Creation00:00:00
Accessing sub arrays00:00:00
Array shape manipulation00:00:00
Operations on Arrays00:00:00
This is one of the most popular libraries in data science. This library is used for data wrangling and analysis. Students will learn in-depth about this library and its usage of the library.
Data Input and Output00:00:00
Operations on Data Frame00:00:00
Describe and manipulate Data Frame00:00:00
Querying the data frame00:00:00
Other important modules00:00:00
Display Data frame – Options and settings00:00:00
Seaborn is the most popular library used in python. In Data Science this library is used for Data Visualization. Students will learn to use this library for visualizing the data in different forms.
Kinds of Plots00:00:00
Styling the plot00:00:00