Python-Data Analysis & Science
This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables
IT professionals who want to enhance their programming skill to next level. Fresher IT graduates want to start career in Python programming. Database developers and administrators. Network and System engineers. Software testing professionals.
After completing this course, you will be able to learn :
- Learn Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python.
- Learndata manipulation and cleaning techniques using the popular python pandas data science library.
- Learn the abstraction of the Series and DataFrame as the central data structures for data analysis.
There are no pre-requisites required for attending this Course.
This is a Three days course syllabus and is a classroom-based instructor-led one.
Course Outline / Content :
The following Modules are included in this course :
- Module 1: Basics of Python for Data Analysis
- Module 2: Python libraries and data structures
- Module 3: Exploratory analysis in Python using Pandas
- Module 4: Data Munging in Python using Pandas
Course Objectives :
- An introduction to the field of data science, review common Python functionality and features which data scientists use.
- Learn the fundamentals of one of the most important toolkits Python has for data cleaning and processing – pandas.
- Learn how to read in data into DataFrame structures, how to query these structures, and the details about such structures are indexed.
- Deepen your understanding of the python pandas library by learning how to merge DataFrames, generate summary tables, generate summary tables, group data into logical pieces, and manipulate dates
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