Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
17 Hour(s) 40 Minute(s)
Language
English
Taught by
Prashant Shekhar
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
2 views
Course Overview
Data Analysis with Python libraries - NumPy, Pandas, MatplotLib and Seaborn | 150+ MCQ Question | 2 Projects
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.
Course Content
- 13 section(s)
- 139 lecture(s)
- Section 1 Introduction to NumPy
- Section 2 Pandas Basic, Installation & Pandas Series object
- Section 3 Pandas Dataframe object
- Section 4 Data Ingestion and Storage with Pandas
- Section 5 Data Preparation
- Section 6 Data Wrangling
- Section 7 Data Aggregation & Grouping
- Section 8 Visualization with Matplotlib
- Section 9 Visualization with Pandas Object
- Section 10 Visualization with Seaborn
- Section 11 Python Refresher (Video from my Python Programming Bible course )
- Section 12 Projects
- Section 13 Materials used during lecture
What You’ll Learn
- Student will learn data analysis techniques using numpy, pandas, matplotlib and seaborn.
- This course provides theoretical and practical understanding of the key concept of data analysis and data visualization
- The course provides excellent learning tool for creating strategies and correct business decision from the data at hand.
- Student will learn NumPy and Pandas introduction, Data ingestion, Data Preparation, Data Wrangling and Data Aggregation.
- Student will learn Data Visualization techniques using matplotlib, seaborn & pandas object.
Skills covered in this course
Reviews
-
CCorneille Mbiya
I really took my time to go throughout every single slide and for all my time spent, I cannot regret it because, this course has helped me to understand in depth NumPy.
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DDare Afolabi
At least, its being engagging so far
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MMichael Knawby
A great introduction into data analysis with Python.
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MMulakalapalli Umashankar
No words to say Its an amazing course to learn numpy, pandas and visualization in detailed. The way of teaching and concepts ordering is also super good, thanks for the course.
