About this Course:

This intermediate-level training program is specifically designed for Python Programmers, Data Scientists, and Data Engineers. This course provides a comprehensive overview of Applied Python for professionals with fundamental knowledge of Python Programming. This course provides such a professional an incredible learning opportunity to master the core concepts of Python Programming and use its feature for seamless mathematical & scientific computing.

This course overviews Fundamental Python Concepts and Nurture Scripting Skills required to Create & Run Python Programs. Professionals will also get to learn Module & Classes Designing, Unit Test Implementation, Profiling & Benchmarking, JSON & XML Processing, SciPy Classes, NumPy Array Manipulation, PIL Image Manipulation, and many more key concepts. This course will help professionals develop a conceptual understanding of key modules of Python Programming for Scientists & Engineers. On average, a professional Python Data Scientist earns $93,185 annually. 

Course Objective:

The core objective of this course is to help professionals gain a better knowledge and sound understanding of the following key concepts:

• Basic Programs Creation & Running
• Modules & Classes Designing and Programming
• Unit Test Implementation & Performance
• Speeding Up Programs with Profiling and Benchmarks
• JSON and XML Processing and NumPy Array Manipulation
• SciPy Classes of Packages & Sub Packages
• Ad-Hoc Plots, What-Ifs, & Calculations with iPython Notebook
• PIL Image Manipulation and SymPy Equation Solution
• PySpark and SciKit-Learn Advanced Data Science Concepts 

Audience:

This course is specifically tailored for the following group of professionals and interested candidates:

• Python Programmers
• Data Scientists & Data Engineers
• IT Professionals & Experts

Prerequisites:

There are no obligatory prerequisites for the Applied Python for Data Science (TTPS4870) Course. However, it is highly recommended for professionals to have fundamental knowledge & experience of programming.