Python for Data Science for Beginner Hands-on practical Course
What you will learn
How to install Anaconda
Overview of Jupyter Notebook
Module 1 : Variable, Data Types, And Operators
Module 2 : Data Structures: List, Tuple, Set, Dictionary
Module 3 : Control Flow: If Else Statement, While Loop, For Loop
Module 4 : Functions: How to Create Function, Call function, Parameter or Arguments, Built_in Functions, Lambda, Recursion
Module 5 : File Handling: Creating, Reading, Updating, and Deleting files
Module 6 : NumPy: Install & Import NumPy, Create O D Array, 1D Array, 2D Array, 3D Array, Slicing, Shape, Reshape, Joining, Splitting, Searching, Sorting
Module 7 : Pandas: Install &Import Pandas, Read Files, Analyzing Data Frame, Cleaning Data
Modules 8 : Matplotlib: Install & Import Matplotlib & Pyplot, Plotting x and y, Markers, Creating Lines, Style, Scatter Plots, Bar Charts, Histogram, Pie Chart.
Description
Why is Python Essential for Data Science and Data Analysis?
There are numerous reasons why Python is extremely essential for data analysis, a few of them are:
flexibility
Easy-to-learn
Open Source
Well-supported
Learn Python for Data Science
Those who wish to start learning Python for data science or upskill themselves can enroll in a Python certification course. Data Science YF offers the Course.
Data science and analytics have applications across different industries today. Some of these include healthcare, financial and insurance services, e-commerce, retail, entertainment, education, and more. This is the reason why there are big opportunities in data science and data analytics, which are expected to grow further in the near future.
You will learn about Python for Data Science from zero to advance all Hands-on practical work in Jupiter NoteBook…
Course Overview
How to install Anaconda
Overview of Jupyter NoteBook
Module 1 : Variable, Data Types, And Operators
Module 2 : Data Structures
Data Structures: List, Tuple, Set, Dictionary
Module 3 : Control Flow
Control Flow: If Else Statement, While Loop, For Loop
Module 4 : Functions
Functions: How to Create Function, Call function, Parameter or Arguments, Built_in Functions, Lambda, Recursion
Module 5 : File Handling
File Handling: Creating, Reading, Updating, and Deleting files
Module 6: NumPy
NumPy: Install & Import NumPy, OD Array, 1D Array, 2D Array, 3D Array, Slicing, Shape, Reshape, Joining, Splitting, Searching, Sorting
Module 7 : Pandas
Pandas: Install &Import Pandas, Read Files, Analyzing Data Frame, Cleaning Data
Modules 8 : Matplotlib
Matplotlib: Install & Import Matplotlib & Pyplot, Plotting x and y, Markers, Creating Lines, Style, Scatter Plots, Bar Charts, Histogram, Pie Chart.
Content