The Data Analyst Course: Complete Data Analyst Bootcamp

Complete Data Analyst Training: Python, NumPy, Pandas, Data Collection, Preprocessing, Data Types, Data Visualization
4.52 (21598 reviews)
Udemy
platform
English
language
Data & Analytics
category
instructor
The Data Analyst Course: Complete Data Analyst Bootcamp
153 749
students
21.5 hours
content
Apr 2025
last update
$149.99
regular price

What you will learn

The course provides the complete preparation you need to become a data analyst

Fill up your resume with in-demand data skills: Python programming, NumPy, pandas, data preparation - data collection, data cleaning, data preprocessing, data visualization; data analysis, data analytics

Acquire a big picture understanding of the data analyst role

Learn beginner and advanced Python

Study mathematics for Python

We will teach you NumPy and pandas, basics and advanced

Be able to work with text files

Understand different data types and their memory usage

Learn how to obtain interesting, real-time information from an API with a simple script

Clean data with pandas Series and DataFrames

Complete a data cleaning exercise on absenteeism rate

Expand your knowledge of NumPy – statistics and preprocessing

Go through a complete loan data case study and apply your NumPy skills

Master data visualization

Learn how to create pie, bar, line, area, histogram, scatter, regression, and combo charts

Engage with coding exercises that will prepare you for the job

Practice with real-world data

Solve a final capstone project

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Our Verdict

The Data Analyst Course: Complete Data Analyst Bootcamp on Udemy is a valuable resource for aspiring data analysts seeking to enhance their skills with Python, NumPy, pandas, and real-world data scenarios. Although there are some minor issues related to clarity in code exercises and model answers, the course provides an engaging experience overall with rich content that helps learners practice and master essential techniques for data analysis. While not perfect, this course is a worthwhile pursuit due to its comprehensive approach and practical application of key concepts.

What We Liked

  • Comprehensive coverage of key data analysis topics with Python, NumPy, and pandas
  • Incorporates coding exercises to practice essential skills
  • Real-world data and capstone project provide practical experience
  • Professional presentation and clear visuals

Potential Drawbacks

  • Inconsistency between section names in course outline and actual content
  • Limited guidance for code exercises and no answers to challenges
  • Some code exercises can produce incorrect results due to ambiguous requirements
  • Occasional mismatches between student submissions and the exercise checker's model answers
Related Topics
3570337
udemy ID
15/10/2020
course created date
27/10/2020
course indexed date
Bot
course submited by
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