As part of this development track kids will work on challenges that introduces them to some of the advanced concepts while programming using Python. Some of the benefits of learning Python –

• Pick up a mainstream programming language that is used widely by business and in opensource
• Work in a productive coding environment compared to other languages like C# and Java.
• Work with a programming language which is easy to read, even if you’re not a skilled programmer. Anyone can begin working with the language.
• Work with a programming language which has easy syntax and enjoy writing code
• Dive deep into object oriented programming concepts
• Write programs for embedded devices (Raspberry Pi, ESP32, etc.) and develop/create electronics projects
• Gain skills and understand how to interface with most modern web technologies i.e. API’s, Databases, Rule engines, etc.

For aspiring Data Scientists, Python is probably the most important language to learn because of its rich ecosystem. Python’s major advantage is its breadth. For example, R can run Machine Learning algorithms on a pre-processed dataset, but Python is much better at processing the data in an efficient manner.

As part of this development track kids will work on tutorials that cover most of the items listed from 1 – 6 including a strong focus on 7 – 10 :-

1. Python syntax
2. Conditions and control flow
3. Using functions
4. Strings and console output
5. List manipulation
6. Methods to Iterate through strings, lists and ranges
7. Loops
8. Creating, reading and writing to files
9. Interaction with external API’s
10. Working with JSON formatted data

What is Python –

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python’s simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed.

Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception. When the program doesn’t catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python’s introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective.

Read more at – www.python.org