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data Beginner 21 lessons

Data Science Fundamentals

Transform raw data into insights using Python. Master the scientific stack: Pandas for manipulation, NumPy for math, and Matplotlib for visualization.

Data Science is the art of uncovering hidden value in data. This course introduces the core Python libraries that power the industry. You will learn to clean messy datasets using Pandas, perform vector mathematics with NumPy, and create storytelling visualizations with Matplotlib and Seaborn. We cover the entire Exploratory Data Analysis (EDA) process, preparing you to answer business questions with statistical evidence. This foundation is essential before moving into machine learning or AI.

✅ 100% Free & Lifetime Access
⏱️ 5-Minute Lessons (Bite-sized learning)
🚀 21-Lesson Path (Independent modules)
📱 Mobile Friendly (Learn anywhere)
Data Science Board
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Complete Course Syllabus

  • 1
    NumPy Arrays
    Understanding vectors, matrices, and broadcasting operations.
  • 2
    Pandas DataFrames
    Loading, filtering, sorting, and aggregating tabular data.
  • 3
    Data Cleaning
    Handling missing values, duplicates, and type conversion.
  • 4
    Visualization
    Creating line plots, scatter plots, and histograms.
  • 5
    EDA Projects
    Analyzing a real-world dataset to answer specific questions.

Estimated completion time: 21 lessons • Self-paced learning • Lifetime access

Career Outlook

Estimated Salary
$90k - $130k

Career Paths

Junior Data Scientist $90k-$120k
Data Analyst $75k-$100k
Business Analyst $80k-$110k

What You Will Learn

Clean and manipulate raw datasets using Pandas DataFrames effectively
Perform high-performance numerical calculations using NumPy arrays and matrices
Visualize data trends and distributions using Matplotlib and Seaborn charts
Conduct Exploratory Data Analysis (EDA) to find patterns and anomalies
Import and export data from various sources like CSVs/SQL

Skills You Will Gain

Python Pandas NumPy Matplotlib Data Cleaning

Who Is This For

Aspiring Data Scientists
Analysts learning Python
Business Intelligence Pros

Prerequisites

Python Basics
Basic Statistics

Data Science Fundamentals FAQs

Math heavy?

Requires basic statistics and algebra concepts.

Excel vs Python?

Python handles millions of rows; Excel cannot.

Is this AI?

No, this is the foundation required BEFORE AI.

Tools cost?

Zero. Python and Jupyter are open source.

Need more info?
All Reork courses are 100% free, self-paced, and fully accessible on mobile devices. No prior experience is required. Read our full Platform FAQ.

Tech Stack & Tools

Jupyter Notebook
Anaconda
Pandas
Seaborn
VS Code

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