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Data Analysis Bootcamp: Master Data Science Skills
Highest Rated
Rating: 4.6 out of 5(406 ratings)
33,222 students

Data Analysis Bootcamp: Master Data Science Skills

Learn Data Analysis With Python, Jupyter, Pandas, Dropna - Learn Data Cleaning, Visualization, and Modeling
Highest Rated
Created byLearnify IT
Last updated 4/2026
English

What you'll learn

  • Understand key data concepts like data types, variables, and data cleaning techniques.
  • Master the powerful Python programming language for data manipulation, analysis, and visualization.
  • Discover insightful patterns and trends in your data through exploratory data analysis.
  • Effectively communicate your findings through compelling data visualizations and reports.

Course content

1 section • 17 lectures • 6h 30m total length

  • Introduction11:59
  • Setup and Basic Data Analysis29:21
  • More Basic Data Analysis Commands30:22
  • Counting functions in Data Analysis new update11:26

    Explore counting functions in Python for data analysis using NumPy, including unique values, counts, intersections, unions, set differences, and set xor within a Jupyter notebook workflow.

  • Pandas & Pyplot24:33
  • Linear Regression & Heatmap40:39
  • Dropna21:17
  • PD.Pivot Table24:13
  • DF.Rolling() new update17:59
  • PD.Merge() and PD.Concat()28:15

    Explore PD.merge and PD.concat in pandas to merge and concatenate data frames, compare SQL like joins, handle keys and indices, and build integrated datasets with practical Python examples.

  • PD.Cut() and PD.Gcut()27:23

    Learn how pd.cut and pd.qcut discretize continuous data into bins, compare equal-width and quantile-based bins, and apply them in a practical Jupyter Notebook with sample data.

  • PD.Resample()24:33
  • Scikit-Learn Pipeline27:21

    Learn how the scikit-learn pipeline automates data pre-processing, feature selection, and model training into a reproducible workflow while reducing data leakage and supporting gridsearchcv and randomizedsearchcv.

  • PD.Merge() and PD.Concat()28:15
  • Data.sort_values(by=_column_) part 117:29
  • Class Project 112:01

    Reshape a wide data frame into a long format with pandas melt, keeping product as id var and turning quarterly sales into quarter and sales columns for analysis and visualization.

  • Class Project 213:19

Requirements

  • No experience required

Description

Are you ready to embark on a data-driven journey? This bootcamp is your first step towards becoming a skilled data analyst. Whether you're a beginner or looking to enhance your data skills, this course is designed to provide you with a solid foundation in data analysis.

In this course, you'll learn:

  • Data Fundamentals:

    • Understand key data concepts like data types, variables, and data cleaning techniques.

    • Learn how to handle missing data and outliers.

  • Data Analysis with Python:

    • Master the powerful Python programming language for data manipulation, analysis, and visualization.

    • Utilize libraries like Pandas to efficiently work with data.

  • Data Exploration and Visualization:

    • Discover insightful patterns and trends in your data through exploratory data analysis.

    • Create visually appealing data visualizations using various chart types (histograms, bar charts, scatter plots, etc.).

  • Statistical Analysis:

    • Apply statistical methods to draw meaningful conclusions from your data.

    • Understand hypothesis testing, correlation analysis, and regression analysis.

  • Data Storytelling:

    • Effectively communicate your findings through compelling data visualizations and reports.

    • Present your insights in a clear and concise manner to a non-technical audience.


By the end of this course, you'll be able to:

  • Clean and prepare data for analysis

  • Perform exploratory data analysis to uncover insights

  • Visualize data effectively to communicate findings

  • Apply statistical techniques to draw meaningful conclusions

  • Use Python to automate data analysis tasks

  • Create compelling data stories to drive decision-making


What You'll Get:

  • Lifetime Access to Course Content: Learn at your own pace, anytime, anywhere.

  • High-Quality Video Lectures: Clear and concise explanations of each topic.

  • Practical Exercises: Apply what you've learned with hands-on projects.

  • Certificate of Completion: Showcase your new skills to potential employers.

No prior programming experience is required. This course is designed for beginners and assumes no prior knowledge of data analysis or Python. Enroll now and start your data analysis journey today!

Who this course is for:

  • Anyone who looking to learn data analysis

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