Python is quickly becoming the most widely-used programming language by computer and data scientists today. This course is divided into two distinct sections: coding fundamentals and data science. Students will first develop skills in programming using the python language. Next, they'll explore data science and learn to input, analyze, and graph data using Pandas, Matplotlib, and Sci-Kit learn.
Python is easy to learn and there is no prerequisite math or coding knowledge necessary, making this an excellent course for beginners. Coding and data science are useful skills for anyone interested in finance, journalism/digital media, marketing, and communications.
Take this program as part of a certificate and save:
Learn to graph financial data from the 1800s to present day!
Learn to graph two sets of data on one grid.
Spend Your Summer Programming in Python
Gain real-world programming experience and data science skills in our Python summer camp! Coding know-how will increase your success in high school and college. In this class, you'll strengthen your college application, master computational thinking within real-world contexts, and have fun all at the same time!
This class has been created to help you become fluent quickly in python, the most powerful and popular coding language used by programmers today! Our activity-based curriculum will give you all the skills that two-semester college courses provide.
Break into the World of Data Science
Glassdoor has listed data science as the best job in America for the past 3 years! The skills you learn in this class can be used to analyze any type of data from financial to sport.
Your time is important. This course maximizes your time using hands-on activities and real-world scenarios to explore the challenging curriculum in a way that is both fast and easy! Students begin programming within the first hour of day one!
Learn more about our Python Course
Python is a popular, back-end coding language. Both easy-to-learn and easy-to-use, it’s considered the top coding language in the world. Python is used to build software programs, web applications, online tools, and digital games. Programmers can also use Python to customize popular computer software programs, such as Salesforce.
In 1991, creator Guido Van Rossum designed Python for general purpose programming. It’s most similar to the programming languages C, Java, and Ruby. Python is managed by the Python Software Foundation, and its most recent update was Python 3 in December 2017.
The first half of this course is focused on the fundamentals of Python. Students will learn technical skills, including writing programs in python as well as computation and algorithmic thinking. Students will also learn how to program in pairs and will develop an understanding of coding team dynamics. By the end of part one, students will gain a strong foundation of the universal principles that are applicable to countless coding languages and programming contexts.
The second half of the course is centered upon data science using Python. Data science is a combination of mathematics, statistics, and computer science, and is comprised of three main functions: collecting, analyzing, and visualizing data. In this course, students will learn how to use Python and it's extensive libraries to accomplish all three with precision and ease.
Why Learn Python at NextGen?
Easy to Learn: Python's coding style is considerably intuitive, most notably because of its limited need for lexical syntax and English-like keywords. Unlike Java, Python code does not require punctuation after every line of code. As a result, students are able to master Python quickly, since they can focus on the concepts and paradigms rather than focusing on the syntax.
Used by Many Companies: Python is both well-suited for beginners and marvelously powerful. It is currently being used by many of the world’s top organizations and companies, such as NASA, Amazon, Google, Netflix, Facebook, and Apple. Along with its power, Python's efficiency is outstanding. With only 100 lines of code, Python can achieve at least 500 lines-worth of Java or C++ code.
Extensive Libraries: Along with Python comes a wide variety of libraries, packages, and frameworks, that continue to extend Python's versatility. In fact, libraries like Pandas, NumPy, and Matplotlib are what enable us to use Python for data science. Similarly, the frameworks Django and Flask enable programmers to write Python code for web development.
Community: A language is only as strong and as useful as the number of people who are coding in it. Python has recently surpassed 35 million downloads per year, with an estimated 5 million programmers worldwide using Python as their preferred language. This record-breaking momentum is a testament to Python's impressive strength and speed. Consequently, there is an ever-growing network of proficient Python developers, which makes everything from debugging on Stack Overflow to finding a job in a new city easier and more accessible.
Convenient & Easy Location: NextGen's classes take place at 2 University Plaza Drive in Hackensack, NJ. We're right off of Route 4, central to Bergen County. Our students and families benefit from a large screen TV/display, individual desks, free parking, and free coffee & tea!
Network Effect: NextGen attracts top-notch, highly motivated students who are eager to learn programming. We have a community of talented, hard-working students and alumni, including students from top high schools in NJ such as Dwight Englewood, Frisch School, Bergen Academies, Northern Valley Regional High School, and more. Our alumni are currently attending esteemed colleges and universities, such as NYU Stern, Wharton, Northwestern, Duke, and Michigan, to name a few!
Who should attend our Python Summer Camp?
Our python course is designed for high school students, but college students are welcomed as well! This course serves as an excellent introduction to the world of computer science and to the fundamentals of programming. Anyone who is interested in business, technology, entrepreneurship, journalism, and countless other jobs would benefit from knowing Python code. Students don't even need to know with absolute certainty what type of career they'd like to pursue, since the language can be used for so many different things!
Are there any prerequisites for the Python course?
This course has no math or coding pre-requisites, but students must be comfortable with basic computer skills and have a desire to learn at an advanced level.
Python Course Detailed Overview
- Overview of Coding & Programming: How the Python language works, as well as basic computer organization and architecture.
- Introduction to Programming: Write your first codes to learn python basics, syntax, and dynamic language concepts. Learn how to compile and run programs in the terminal commands, as well as how to use Sublime Text.
- Variables, Data Types, and Operators: Assigning and declaring variables, primitive variable types such as integers, strings, Booleans, and floats, mathematical operators, and/or operators, and proper programming practices such as commenting and variable naming.
- Control Flow: Structuring code: if-else statements, for loops, while loops, global and local variables, nested for loops, switch statements.
- Functions: Creating repeatable code using functions, parameters, arguments, return value, and the motivation behind functions.
- Lists, Strings, Tuples, and Dictionaries: Storing data using lists, declaring an empty list, the index, appending to a list, using loops and lists, manipulating strings, and how key-value pairing works.
- Modular & Object-Oriented Programming: Learn about classes, encapsulation, inheritance, super-class, polymorphism, and how to navigate packages. Understand abstract classes and method overloading.
- Numerical Python: NumPy, arrays, datatype, shape, indexing, slicing, masking, linear algebra, convolution, Fourier.
- Statistical Modeling: Scipy, Discrete and continuous probability distributions, sampling, linear modeling, Monte-Carlo simulation, regression.
- Pandas: Importing CSV and Excel files, series, data frame, shaping, merging, and renaming, methods for data frames, graphing in pandas, API data importing.
- Visualization: Matplotlib, fig and ax, maps, images, sizing, color, styles, limits, log graphs.
- Advanced Topics: Neural networks, artificial intelligence, machine learning, and decision trees.