Data Analysis using python-02Published 5/2026
Created by DADI RAMESH
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner |
Genre: eLearning |
Language: English |
Duration: 34 Lectures ( 9h 31m ) |
Size: 5.71 GB
⚡ Understand Python fundamentals, data structures, and libraries used for data analysis such as NumPy and Pandas.
⚡ Perform data cleaning, preprocessing, transformation, and exploratory data analysis using Python techniques.
⚡ Create visualizations including scatter plots, histograms, box plots, and time series graphs using Matplotlib.
⚡ Apply statistical analysis and machine learning basics to solve real-world data analysis problems using Python.
Requirements❗ No programming experience
DescriptionThis course on Data Analysis Using Python is designed to provide learners with a strong foundation in data analysis, visualization, and interpretation using the Python programming language. The course introduces essential Python concepts and widely used libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn to help learners analyze and process real-world datasets efficiently. It is suitable for students, researchers, working professionals, and beginners who want to develop practical skills in data analytics and data-driven decision making.
The course begins with an introduction to Python programming fundamentals, including variables, data types, operators, lists, tuples, dictionaries, functions, and file handling. Learners will then explore data manipulation techniques using Pandas and numerical computations using NumPy. The course also covers data cleaning, preprocessing, handling missing values, data transformation, and feature extraction methods that are essential for preparing datasets for analysis.
In addition, learners will gain hands-on experience in creating effective visualizations such as scatter plots, histograms, box plots, bar charts, and time series plots using Matplotlib and Seaborn. Descriptive statistics and exploratory data analysis techniques will be used to identify patterns, trends, and insights from datasets.
By the end of this course, learners will be able to perform complete data analysis workflows, generate meaningful insights from data, and build a strong foundation for advanced studies and careers in data science, machine learning, and artificial intelligence.
Who this course is for⭐ Beginners
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