Data Analytics & Visualization Using Python (with Project)
Get the necessary skills to perform efficient data analysis and visualization using Python
Updated on Jun, 2025
Language - English
Development ,Data Science,Python
Lectures -28
Resources -1
Duration -6.5 hours
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Course Description
Welcome to our comprehensive Data Analysis Crash Course, created for people who have done programming in the past and want to quickly brush up on their Python knowledge before diving into data analysis and visualization. This quick-paced course walks you through the fundamentals of Python, Jupyter Notebooks, and robust libraries like NumPy and Pandas to give you a thorough introduction of the principles of commercial data analysis.
During the training, you will learn
- An Introduction to Business Data: Recognize the importance of data in business and the main ideas of analysis.
- Python Basics: Brush up on your understanding of data types, programming concepts, and syntax in Python.
- Data Manipulation: Acquire the skills necessary to manipulate and clean data using Pandas efficiently.
- Exploratory Data Analysis: Learn useful methods for displaying and interpreting data to obtain new perspectives.
- Advanced Topics: Use NumPy to explore linear algebra applications and data collection techniques.
In the course's final assignment, known as the capstone project, you will use your acquired knowledge to solve a practical issue centered around student placement prediction.
This course, which emphasizes practical application through hands-on learning experiences, is ideal for quick revision / exam preparation. To jumpstart your path into commercial data analysis using Python, enroll now!
Goals
- Get proficient at manipulating data with the Pandas library.
- Recognize the fundamentals of corporate data analysis.
- Acquire skills in both visualization and exploratory data analysis (EDA).
- Learn how to use Jupyter Notebooks with ease.
- Use NumPy to investigate more complex subjects like linear algebra and API data collection.
- Complete a capstone project to show off your abilities.
- Take part in practical exercises to gain real-world experience.
- Get ready for tests and expand your data analysis career options.
- Gain self-assurance when evaluating and understanding data.
Prerequisites
Basic Programming Knowledge: Familiarity with basic programming concepts, preferably in Python, including variables, data types, loops, and functions.
Understanding of Fundamental Data Structures: Basic knowledge of common data structures such as lists, dictionaries, and arrays.
Mathematical Foundation: Basic understanding of algebra and statistics to grasp data analysis concepts effectively.
Problem-Solving Skills: Ability to approach and solve problems logically and systematically.
Familiarity with Computer Operations: Basic computer literacy, including file handling and navigating operating systems.
Analytical Thinking: Capacity to think analytically and critically when dealing with data and interpreting results.
While the course is designed for those with some prior programming experience, immediate beginners who are highly motivated and quick learners can also enroll and benefit from the intensive learning approach.
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction to Business and Data
3 Lectures
-
1.1 Overview
08:12
08:12
-
1.2 Key Concepts
15:11
15:11
-
1.3 Python Introduction
19:22
19:22
Python Basics and Jupyter Notebooks
4 Lectures
Operators and Conditionals
2 Lectures
Loops and function
2 Lectures
Object-Oriented Programming (OOP) and NumPy
3 Lectures
Pandas Library and Data Manipulation
3 Lectures
Working with Files and Data Importing
3 Lectures
Data Cleaning and Preprocessing
2 Lectures
Exploratory Data Analysis (EDA)
2 Lectures
Advanced Topics
3 Lectures
Capstone Project
1 Lectures
Instructor Details
Selfcode Academy
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