Intro to Python Programming May registration closes on June 10, 2022

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intermediate Python

Class description

This is an instructor-led course to introduce you to the Python programming language. Python is one of the most popular programming languages used in industries ranging from gaming to finance. Python is an interpreted, object-oriented high-level programming language, which has recently become a popular tool in industry and in academia.


Python is free to use, easy to install and learn and its open source. In this course, you will learn to create programs, functions, complex data structures and to collect user input with Python. Furthermore, you will learn to read and write from external sources such as files and databases By learning these concepts, students will have a starting point to learn a few of the many ways that Python is utilized from basic reporting to complex machine learning solutions and much more.

Uses of intermediate Python

  • The Python programming language is used by business analysts, software developers to analyze data and to create captivating yet insightful data visualizations
  • The Python programming language can be used for developing both desktop, web and mobile applications.
  • Python can be used for creating Windows, UNIX and Mac applications, from simple console and web-based to
  • elaborate graphic interfaces for video games.
  • Also, you can use Python for developing complex scientific and numeric applications for Machine Learning, Robotics and Finance


Course objectives

  • Introduce students to the basics of Python.
  • Provide students with the hands-on Python programming building block skills needed to develop applications
  • Create working Python scripts following best practices
  • Use python data types appropriately
  • Read and write files with both text and binary data
  • Search and replace text with regular expressions
  • Get familiar with the standard library and its work-saving modules
  • Create "real-world", basic level professional Python applications
  • Know when to use collections such as lists, dictionaries, and sets
  • Understand Pythonic features such as comprehensions and iterators
  • Write robust code using exception handling

Course Format

This course is a 50% hands-on labs to 50% lecture ratio with engaging instruction, demos, group discussions,

labs, and project work including a capstone assignment.

Class Syllabus

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Class Syllabus

Module 1 - Introduction to Python Crash Course

  •  System set up
  • Data Structures, Numbers, Strings and Loops
  • Input / Output Operations
  • Algorithms and conditional functions
  • Data Analysis  Modules (Numpy, Pandas)
  • Pandas Dataframes and Series
  • Pandas Operations

Module 2 - Extracting Data From the Internet

  • Introduction to Web Scraping
  • Web scraping with the Beautiful Soup Library
  • Inspecting a website and parsing HTML
  • Finding specific elements on a website
  • Saving  and using website elements

Module 3 - Chat Bot

  • Introduction to Natural Language Processing (NLP)
  • Importing and using Chatter Bot libraries
  • Building your first chatbot

Module 4 - Data Visualization

  • Basic Graphs and Matplotlib and Seaborn
  • Interactive Graphs and Bokeh
  • Building dashboards with Dash and Plotly

Module 5 - Exploratory data analysis (EDA) projects

  • Loading datasets 
  • Handling missing values
  • Removing duplicate values
  • Working with outliers in the data
  • Normalizing and scaling (Numeric variables)
  • Encoding categorical variables (Dummy variables)
  • Bivariate analysis

Module 6 - Twitter Feeds and Data Mining

  • Setting up Tweepy
  • Accessing the Twitter Api
  • Using Twitter data in your application

Module 7 - Machine Learning & Predictive modeling

  • Introduction to Machine Learning
  • Importing and learning SciPy
  • Learn to use Machine Learning algorithms
  • Loading training and testing data
  • Prediction modeling using machine learning

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