Key Highlights
- 24 Hours of Case Studies on Real-life Scenarios
- 8 Sessions of 3 hours each on weekends
- 12 Sessions of 2 hours each on weekdays
- Practical Assignments
- Lifetime Access to Learning Management System
- 24x7 Expert Support
- Course Completion Certificate
- Online Forum for Discussions
Available Courses Delivery
This course is available in the following formats:
Course Overview
This course is designed to train learners in Python programming concepts, such as, Data & file operations in Python, Object-oriented concepts in Python, and various Python libraries. It educates about different types of data, data visualization, python scripting, and iPython notebooks.
Course Objectives
- Educate about data visualization
- Train in writing Python scripts and unit test code
- Teach about downloading and analyzing data
- Acquaint learners with various techniques to handle different types of data
- Introduction to numerous types of data-Ordinal, Categorical, and Encoding
- Educate about iPython notebooks
- Establish proficiency in presenting step-by-step data analysis
Career Benefits
- Better remuneration as a Python Expert
- Demonstrate expertise in Data Science field
- Multi-industry opportunities
Prerequisites
- Prior knowledge of Computer Programming terminologies
Who should take up?
- Project Managers
- Business Analysts
- Business Intelligence Managers
- Statisticians and Analysts
- Data Scientists
- Data Analysts
- Programmers
- Developers
- Technical Leads
- Architects
Course Content
- Overview of Python
- The Companies using Python
- Other applications in which Python is used
- Discuss Python Scripts on UNIX/Windows
- Variables
- Operands and Expressions
- Conditional Statements
- Loops
- Command Line Arguments
- Writing to the screen
- Python files I/O Functions
- Lists and related operations
- Tuples and related operations
- Strings and related operations
- Sets and related operations
- Dictionaries and related operations
- Functions
- Function Parameters
- Global variables
- Variable scope and Returning Values
- Lambda Functions
- Object-Oriented Concepts
- Standard Libraries
- Modules Used in Python (OS, Sys, Date and Time etc.)
- The Import statements
- Module search path
- Package installation ways
- Errors and Exception Handling
- Handling multiple exceptions
- NumPy - arrays
- Operations on arrays
- Indexing slicing and iterating
- Reading and writing arrays on files
- Pandas - data structures & index operations
- Reading and Writing data from Excel/CSV formats into Pandas
- matplotlib library
- Grids, axes, plots
- Markers, colours, fonts and styling
- Types of plots - bar graphs, pie charts, histograms
- Contour plots
- Basic Functionalities of a data object
- Merging of Data objects
- Concatenation of data objects
- Types of Joins on data objects
- Exploring a Dataset
- Analyzing a dataset
- GUI Programming
- Ipywidgets package
- Numeric Widgets
- Boolean Widgets
- Selection Widgets
- String Widgets
- Date Picker
- Color Picker
- Container Widgets
- Creating a GUI Application
- MySQL DB access
- Network programming
- Multithreading
- Use of Folium Library
- Use of Pandas Library
- Flowchart of Web Map application
- Developing Web Map using Folium and Pandas
- Reading information from Dataset and represent it using Plots
- Beautiful Soup Library
- Requests Library
- Scrap all hyperlinks from a webpage, using Beautiful Soup & Requests
- Plotting charts using Bokeh Plotting scatterplots using Bokeh
- Image Editing using OpenCV
- Face detection using OpenCV
- Motion Detection and Capturing Video
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Duration Hours
LevelAdvanced
Modules154