Data Analysis with Python, Pandas and NumPy
Data Analysis with Python libraries - NumPy, Pandas, MatplotLib and Seaborn | 150+ MCQ Question | 2 Projects
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Data Analysis with Python, Pandas and NumPy udemy course
Data Analysis with Python libraries - NumPy, Pandas, MatplotLib and Seaborn | 150+ MCQ Question | 2 Projects
What you'll learn:
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Use Python for Data Science and Machine Learning
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Learn to use Pandas for Data Analysis
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Learn to use NumPy for Numerical Data
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Learn to use Seaborn for statistical plots
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Learn to use Matplotlib for Python Plotting
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You will learn how to use Jupyter Notebook for exploratory computations using python.
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You will learn basic and advanced features in NumPy (Numerical Python)
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You will learn various data analysis tools in Pandas library.
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You will learn the essential tools for load, clean, transform, merge, and reshape data.
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You will learn how to create informative visualizations with matplotlib, seaborn and Pandas
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You will learn how to analyze and manipulate time series data.
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You will learn how to handle real world data analysis, including data preparation and exploration.
Requirements:
- It is advantageous to have basic python knowledge, but it is not required to understand the material in this course. However, people with no previous basic knowledge of python need to focus first on module 2, 3, 4, and 5, that would be enough to comprehend the rest material in this course.
Description:
Data Analysis with Python is for everyone who would like to create meaningful insight out of the data with the power of Numpy, Pandas, Matplotlib & Seaborn. The course has the right recipe to equip student with the right set of skill to ingest, clean, merge, manipulate, transform and finally visualize the data to create the meaning out of the data at hand.
The goal of this course is many fold :
- To provide theoretical and practical understanding of data analysis with Python package like NumPy and Pandas.
- To provide the knowledge of visualization tool ( matplotlib and seaborn ) so that one will be able to visualize and make correct decision based on the data.
- And finally practice with real life data to feel confident of the topic and be able to ready to work on data analysis project or interview.
The whole project is divided into following module :
- NumPy introduction
- Pandas introduction (Series and dataframe objects )
- Data ingestion & Storage ( CSV, Excel, SQLite, JSON, HTML, Pickle and HDF5 storage etc. )
- Data Preparation ( Identify missing data, Handle missing data, handling duplicate data, Data transformation, Manipulating Row & Columns, Bucket Analysis, Outlier detection, Sampling, Creating dummy variable etc. )
- Data Wrangling ( Data Aggregation, Merging, Joins - Inner, Outer, Left & Right join, Join, Concatenate, Pivot, Melt etc. )
- Data Aggregation (Split, Apply & Combine, GroupBy clause, Binning data, Pivot table and Cross tabulations etc. )
- Visualization ( MatplotLib, Pandas Object visualization, Seaborn )
- Project - Practice data analysis with real life datasets.
Who this course is for:
- Python developers who aim to learn data ingestion, data analysis and data visualization
- Data analyst who would like to derive business insight out the data.
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Course Details:
- 17.5 hours on-demand video
- 3 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of completion
Data Analysis with Python, Pandas and NumPy udemy free download
Data Analysis with Python libraries - NumPy, Pandas, MatplotLib and Seaborn | 150+ MCQ Question | 2 Projects
Demo Link: https://www.udemy.com/course/python-for-data-analysis-numpy-pandas-matplotlib-seaborn/
