Data Analysis with Python

Course level:All Levels
Course Duration: 60h

About Course

In this course, you will learn how to analyze data using Python. During this course, you will learn starting from the basics of Python to exploring different types of data. You will also learn, how to load data from different sources such as CSVs. You will also learn how to prepare data for analysis, perform statistical data analysis, and create meaningful data visualization. You will learn libraries such as Numpy, Pandas, Matplotlib, and Seaborn to process and visualize data. We will start with the installation of Python using Anaconda distribution. You will learn how to use Spyder, iPython, and Jupyter notebook. We will cover the fundamentals of Python that are critical for data analysis and machine learning projects. You will learn NumPy which includes multidimensional arrays with broadcasting capabilities, mathematical functions, linear algebra functionalities, and tools to read and write array data to disk. You will also learn pandas library that includes series, DataFrame, Indexing, summarizing, and computing descriptive statistics.
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What I will learn?

  • Course in the Hindi Language
  • 100% online course
  • Hands-on Projects
  • Earn a sharable certificate upon completion
  • Affordable Program
  • Complete the course according to your schedule
  • Get tangible career benefits after completion of the course
  • Approximately 60 hours of course content
  • No hard prerequisites

Course Curriculum

Course Introduction

  • About the Course
    05:23

Introduction to Programming
Topics - Computational Thinking, Algorithm, Fixed vs Stored Program, Programs, What is Programming Language, Primitive Constructs, Programming Error Types, Impact of Programming Errors

Introduction to Python
Topics - Introduction to Python, Python Essential Libraries

Essential Python Libraries
Topics - NumPy, pandas, matplotlib, IPython and Jupyter, scipy, scikit-learn, statsmodels

Python Installation
Topics - Install Python, Anaconda, Install Anaconda, Package included in Anaconda

Miniconda and Conda
Topic - Miniconda and Conda, Conda, pip, Conda versus pip

Anaconda Navigator
Topic - About Anaconda Navigator

Jupyter Notebook
Topics - Introduction to Jupyter Notebook, Notebook Document, Starting Notebook Server, Create new notebook document, Notebook user interface, Structure of a notebook

Spyder IDE
Topic - About Spyder, Editor Pane, IPython Console, Variable Explorer, Help Pane, Plots Pane, Files Pane, History Pane

IPython
Topic - IPython Interpreter, Tab Completion, Introspection, %run command, magic Commands, matplotlib Integration

Python Language Semantics
Topics - Indentation, Objects, Comments, Variables and Assignments, Dynamic Reference, Attributes & Methods, Duck Typing, Import, Binary Operators, Mutable and Immutable Objects

Scalar Types
Topics - Scalar, Numeric Type, String, Boolean, Type Casting, None, Date Time, Input

Control Flow
Topics - Branching Programs, Iterations, For Loops, While Loops, pass, range, Ternery Expressions

Data Structures – tuple
Topics - Tuples, Unpacking Tuple, Tuple Methods

Data Structures – list
Topics - Lists, Adding and Removing Elements, Concatenation and Combining List, Sorting, Slice

₹2,000.00
  • Level
    All Levels
  • Duration
    60 hours
  • Last Updated
    January 2, 2023

Material Includes

  • 60 hours of digital content
  • On-demand videos
  • Graded quizzes and assignments
  • 4 Hands-on Projects
  • Unlimited access for 1 year
  • Certification on completion

Requirements

  • Understand Python Programming Concepts
  • Concepts of NumPy and pandas
  • 4 Projects using Statistical Data Analysis
  • Data Visualization with matplotlib and seaborn
  • Anaconda, iPython, JuPyter, Spyder

Target Audience

  • School Students
  • Engineering Students
  • Management Students
  • Working Professionals
  • Faculty members and teachers

Skills you will gain

Anaconda Data Analytics Data Science Exploratory Data Analysis Jupyter matplotlib NumPy pandas scipy seaborn Statistical Data Analysis