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Data Analyst in Python for beginners

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Data Analyst in Python for beginners, available at $27.99, has an average rating of 4.71, with 46 lectures, based on 7 reviews, and has 640 subscribers.

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You will learn about Understand the fundamentals of data analysis and its role in decision-making. Acquire proficiency in using Python programming language for data analysis tasks. Learn to handle data acquisition from various sources and formats. Master data cleaning techniques to ensure data quality and reliability. Explore exploratory data analysis (EDA) techniques to uncover patterns, trends, and relationships in data. Apply statistical analysis techniques to draw meaningful conclusions and make data-driven decisions. Develop skills in data preprocessing and transformation for analysis purposes. Gain proficiency in using popular Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn for data analysis. Learn to create informative and visually appealing data visualizations using Python. Understand the basics of machine learning and its applications in data analysis. Develop proficiency in working with real-world datasets and solving data analysis problems. Gain experience in presenting data analysis findings and insights effectively. This course is ideal for individuals who are Beginners: This course is perfect for beginners who are new to the field of data analysis and want to kickstart their journey by learning Python as their primary tool. No prior programming or data analysis experience is required, making it accessible to those with diverse backgrounds. or Aspiring Data Analysts: If you aspire to become a data analyst or work with data in your professional career, this course will provide you with a strong foundation. You will learn the fundamental concepts, techniques, and best practices needed to excel as a data analyst using Python. or Professionals Seeking to Enhance Data Analysis Skills: Professionals from various domains such as business, marketing, finance, social sciences, research, and more can benefit from this course. If you want to enhance your data analysis skills, learn Python as a data analysis tool, and derive meaningful insights from data, this course is for you. or Graduates and Students: Recent graduates and students who are interested in data analysis and want to acquire in-demand skills can enroll in this course. It will provide you with a valuable skill set that can boost your employability in various industries. or Self-Learners and Data Enthusiasts: If you have a passion for data and love exploring and analyzing information, this course will equip you with the necessary skills to work with data effectively. It is suitable for self-learners who want to enhance their knowledge and capabilities in data analysis. or Working Professionals Seeking to Upskill: If you are a working professional looking to upskill or transition into a data analysis role, this course will provide you with the necessary skills and knowledge to make that transition. You will learn practical techniques and gain hands-on experience that can be directly applied in your professional work. It is particularly useful for Beginners: This course is perfect for beginners who are new to the field of data analysis and want to kickstart their journey by learning Python as their primary tool. No prior programming or data analysis experience is required, making it accessible to those with diverse backgrounds. or Aspiring Data Analysts: If you aspire to become a data analyst or work with data in your professional career, this course will provide you with a strong foundation. You will learn the fundamental concepts, techniques, and best practices needed to excel as a data analyst using Python. or Professionals Seeking to Enhance Data Analysis Skills: Professionals from various domains such as business, marketing, finance, social sciences, research, and more can benefit from this course. If you want to enhance your data analysis skills, learn Python as a data analysis tool, and derive meaningful insights from data, this course is for you. or Graduates and Students: Recent graduates and students who are interested in data analysis and want to acquire in-demand skills can enroll in this course. It will provide you with a valuable skill set that can boost your employability in various industries. or Self-Learners and Data Enthusiasts: If you have a passion for data and love exploring and analyzing information, this course will equip you with the necessary skills to work with data effectively. It is suitable for self-learners who want to enhance their knowledge and capabilities in data analysis. or Working Professionals Seeking to Upskill: If you are a working professional looking to upskill or transition into a data analysis role, this course will provide you with the necessary skills and knowledge to make that transition. You will learn practical techniques and gain hands-on experience that can be directly applied in your professional work.

Enroll now: Data Analyst in Python for beginners

Summary

Title: Data Analyst in Python for beginners

Price: $27.99

Average Rating: 4.71

Number of Lectures: 46

Number of Published Lectures: 46

Number of Curriculum Items: 46

Number of Published Curriculum Objects: 46

Original Price: $27.99

Quality Status: approved

Status: Live

What You Will Learn

  • Understand the fundamentals of data analysis and its role in decision-making.
  • Acquire proficiency in using Python programming language for data analysis tasks.
  • Learn to handle data acquisition from various sources and formats.
  • Master data cleaning techniques to ensure data quality and reliability.
  • Explore exploratory data analysis (EDA) techniques to uncover patterns, trends, and relationships in data.
  • Apply statistical analysis techniques to draw meaningful conclusions and make data-driven decisions.
  • Develop skills in data preprocessing and transformation for analysis purposes.
  • Gain proficiency in using popular Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn for data analysis.
  • Learn to create informative and visually appealing data visualizations using Python.
  • Understand the basics of machine learning and its applications in data analysis.
  • Develop proficiency in working with real-world datasets and solving data analysis problems.
  • Gain experience in presenting data analysis findings and insights effectively.

Who Should Attend

  • Beginners: This course is perfect for beginners who are new to the field of data analysis and want to kickstart their journey by learning Python as their primary tool. No prior programming or data analysis experience is required, making it accessible to those with diverse backgrounds.
  • Aspiring Data Analysts: If you aspire to become a data analyst or work with data in your professional career, this course will provide you with a strong foundation. You will learn the fundamental concepts, techniques, and best practices needed to excel as a data analyst using Python.
  • Professionals Seeking to Enhance Data Analysis Skills: Professionals from various domains such as business, marketing, finance, social sciences, research, and more can benefit from this course. If you want to enhance your data analysis skills, learn Python as a data analysis tool, and derive meaningful insights from data, this course is for you.
  • Graduates and Students: Recent graduates and students who are interested in data analysis and want to acquire in-demand skills can enroll in this course. It will provide you with a valuable skill set that can boost your employability in various industries.
  • Self-Learners and Data Enthusiasts: If you have a passion for data and love exploring and analyzing information, this course will equip you with the necessary skills to work with data effectively. It is suitable for self-learners who want to enhance their knowledge and capabilities in data analysis.
  • Working Professionals Seeking to Upskill: If you are a working professional looking to upskill or transition into a data analysis role, this course will provide you with the necessary skills and knowledge to make that transition. You will learn practical techniques and gain hands-on experience that can be directly applied in your professional work.

Target Audiences

  • Beginners: This course is perfect for beginners who are new to the field of data analysis and want to kickstart their journey by learning Python as their primary tool. No prior programming or data analysis experience is required, making it accessible to those with diverse backgrounds.
  • Aspiring Data Analysts: If you aspire to become a data analyst or work with data in your professional career, this course will provide you with a strong foundation. You will learn the fundamental concepts, techniques, and best practices needed to excel as a data analyst using Python.
  • Professionals Seeking to Enhance Data Analysis Skills: Professionals from various domains such as business, marketing, finance, social sciences, research, and more can benefit from this course. If you want to enhance your data analysis skills, learn Python as a data analysis tool, and derive meaningful insights from data, this course is for you.
  • Graduates and Students: Recent graduates and students who are interested in data analysis and want to acquire in-demand skills can enroll in this course. It will provide you with a valuable skill set that can boost your employability in various industries.
  • Self-Learners and Data Enthusiasts: If you have a passion for data and love exploring and analyzing information, this course will equip you with the necessary skills to work with data effectively. It is suitable for self-learners who want to enhance their knowledge and capabilities in data analysis.
  • Working Professionals Seeking to Upskill: If you are a working professional looking to upskill or transition into a data analysis role, this course will provide you with the necessary skills and knowledge to make that transition. You will learn practical techniques and gain hands-on experience that can be directly applied in your professional work.

The course is designed to equip students with the essential skills and knowledge required to become proficient data analysts using the Python programming language. This comprehensive course caters to individuals who aspire to work with data, derive meaningful insights, and make data-driven decisions. No prior experience in programming or data analysis is required.

Throughout this course, students will learn the core concepts and techniques necessary for effective data analysis using Python. From data acquisition and cleaning to exploratory data analysis, statistical analysis, and data visualization, students will gain hands-on experience in performing a wide range of data analysis tasks using popular Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn.

Course Objectives:

Understand the fundamentals of data analysis and the role of a data analyst in various industries.

Acquire proficiency in using Python programming language for data analysis tasks.

Develop skills in acquiring, cleaning, and preprocessing data for analysis.

Learn exploratory data analysis (EDA) techniques to uncover patterns, trends, and relationships in datasets.

Apply statistical analysis techniques to draw meaningful conclusions and make data-driven decisions.

Master the art of data visualization to effectively communicate insights and findings.

Gain the practical Python skills hands-on experience in working with real-world datasets through practical exercises and projects.

Course Curriculum

Chapter 1: Introduction to Data Analysis

Lecture 1: Course Introduction

Lecture 2: Overview of data analysis process

Lecture 3: Role of a data analyst

Lecture 4: Introduction to Python for data analysis

Chapter 2: Python Setup

Lecture 1: What is Python

Lecture 2: What is Jupyter Notebook

Lecture 3: Installing Jupyter Notebook Server

Lecture 4: Running Jupyter Notebook Server

Lecture 5: Jupyter Notebook Components

Lecture 6: Creating a new notebook

Lecture 7: Python Fundamentals

Lecture 8: Hands on : Python Variables

Chapter 3: Data Manipulation with Pandas

Lecture 1: Introduction to the Pandas library

Lecture 2: Loading and exploring datasets

Lecture 3: Data cleaning and preprocessing techniques

Lecture 4: Handling missing data and outliers

Lecture 5: Data transformation and aggregation

Chapter 4: Data Visualization with Matplotlib and Seaborn

Lecture 1: Introduction to data visualization

Lecture 2: Plotting with Matplotlib

Lecture 3: Creating advanced visualizations with Seaborn

Lecture 4: Customizing plots, adding labels, and annotations

Chapter 5: Exploratory Data Analysis (EDA)

Lecture 1: Understanding the importance of EDA

Lecture 2: Descriptive statistics and summary metrics

Lecture 3: Univariate, bivariate, and multivariate analysis

Lecture 4: Identifying patterns, trends, and outliers

Chapter 6: Statistical Analysis with Python

Lecture 1: Introduction to statistical analysis

Lecture 2: Hypothesis testing and significance

Lecture 3: Confidence intervals and p-values

Lecture 4: Correlation and regression analysis

Lecture 5: Introduction to machine learning algorithms for prediction

Chapter 7: Working with Real-World Datasets

Lecture 1: Accessing and acquiring data from various sources

Lecture 2: Web scraping for data collection

Lecture 3: Working with structured and unstructured data

Lecture 4: Handling large datasets efficiently

Chapter 8: Data Analysis and Visualization with Python

Lecture 1: Tabular Data

Lecture 2: Exploring Pandas DataFrame

Lecture 3: Manipulating a Pandas DataFrame

Lecture 4: What is data cleaning

Lecture 5: Basic data cleaning process

Lecture 6: What is data visualization

Lecture 7: Visualizing Qualitative Data

Lecture 8: Visualizing Quantitative Data

Chapter 9: Data Analysis Project

Lecture 1: Applying the learned concepts to a real-world data analysis project

Lecture 2: Data exploration, cleaning, and visualization

Lecture 3: Statistical analysis and insights extraction

Lecture 4: Presenting findings and communicating results effectively

Instructors

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Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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