Introductory Python

Introductory Python

Introductory Python

This is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web.

Course Overview

This is a class for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web.

Due to COVID-19 and with an abundance of caution, all of our courses are being conducted remotely.
* Tuition paid for part-time courses can be applied to the Data Science Bootcamps if admitted within 9 months.
April Session
$1590.00
April Session
Apr 20 - May 13, 2020, 7:00-9:30pm
This class is held on Mondays and Wednesdays
June Session
$1590.00
Early bird pricing
$1510.50
June Session
Jun 2 - Jun 25, 2020, 7:00-9:30pm
This class is held on Tuesdays and Thursdays

Date and Time

April Session

This class is held on Mondays and Wednesdays
Apr 20 - May 13, 2020, 7:00-9:30pm
Day 1: April 20, 2020
Day 2: April 22, 2020
Day 3: April 27, 2020
Day 4: April 29, 2020
Day 5: May 4, 2020
Day 6: May 6, 2020
Day 7: May 11, 2020
Day 8: May 13, 2020
$1590.00
Enroll Now

June Session Early-bird Pricing!

This class is held on Tuesdays and Thursdays
Jun 2 - Jun 25, 2020, 7:00-9:30pm
Day 1: June 2, 2020
Day 2: June 4, 2020
Day 3: June 9, 2020
Day 4: June 11, 2020
Day 5: June 16, 2020
Day 6: June 18, 2020
Day 7: June 23, 2020
Day 8: June 25, 2020
$1590.00$1510.50
Enroll Now

Instructors

Hasan Aljabbouli
Hasan Aljabbouli
Hasan Aljabbouli is an Assistant Professor in Computer Science. He obtained his Master's and Doctorate in Artificial Intelligence from Cardiff University in the United Kingdom and his Bachelor's in Engineering in Information Technology from Homs University. He worked for different universities and has published many scholastic materials in Data Mining and Machine Learning and its applications. In addition to his academic experience, Hasan received two patents and earned relevant experiences participating in various technical projects.
Alexander Baransky
Alexander Baransky
Alex received his degree in Environmental Biology from Columbia University. He has experience with multiple computer languages including Python, R, and SQL. As an engineer at heart and biologist through training, Alex is passionate about animal behavior and finding innovative ways to use data science in the field of biology.

Product Description


Overview

 

This Introductory Python class is designed for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web.

Details

 


Goals

 

This Introductory Python class runs over four weeks, with five hours of class per week (split into 2 ½ hour evening classes). Classes will be given in a lab setting, with student exercises mixed with lectures. Students should bring a laptop to class. There will be a modest amount of homework after each class. Due to the focused nature of this course, there will be no individual class projects but the instructors will be available to help students who are applying Python to their own work outside of class.

Certificate

Certificates are awarded at the end of the program at the satisfactory completion of the course.

Students are evaluated on a pass/fail basis for their performance on the required homework and final project (where applicable). Students who complete 80% of the homework and attend a minimum of 85% of all classes are eligible for the certificate of completion.


Syllabus

Unit 1: List manipulation

  • Simple values and expressions
  • Defining functions, using ordinary syntax and lambda syntax
  • Lists
    • Built-in functions and subscripting
    • Nested lists
  • Functional operators: map and filter
  • List Comprehensions
  • Multiple-list operations: map and zip
  • Functional operators: reduce

Unit 2: Strings and simple I/O

  • Characters
  • Strings as lists of characters
  • Built-in string operations
  • Input files as lists of strings
  • Print statement
  • Reading data from the web
    • Using the requests package
    • String-based web scraping (e.g. handling csv files)

Unit 3: Control structures

  • Statements vs. expressions
  • For loops
    • Variables in for loops
  • if statements
    • Simple and nested if statements
    • Conditional expressions in lambda functions
  • While loops
    • break and continue

Unit 4: Data Analysis Packages

  • NumPy
    • Ndarray
    • Subscripting and slicing
    • Operations
  • Pandas
    • Data Structure
    • Data Manipulation
    • Grouping and Aggregation

Preparation – How to set up Python environment

[IMPORTANT] In the class we will use Python 3. If you are following this video to set up Python environment, please make sure you download the Python 3.X version starting from 1 min 23 s in the video.

Reviews

There are no reviews yet.

Instructors

Hasan Aljabbouli
Hasan Aljabbouli
Hasan Aljabbouli is an Assistant Professor in Computer Science. He obtained his Master's and Doctorate in Artificial Intelligence from Cardiff University in the United Kingdom and his Bachelor's in Engineering in Information Technology from Homs University. He worked for different universities and has published many scholastic materials in Data Mining and Machine Learning and its applications. In addition to his academic experience, Hasan received two patents and earned relevant experiences participating in various technical projects.
Alexander Baransky
Alexander Baransky
Alex received his degree in Environmental Biology from Columbia University. He has experience with multiple computer languages including Python, R, and SQL. As an engineer at heart and biologist through training, Alex is passionate about animal behavior and finding innovative ways to use data science in the field of biology.

Product Description


Overview

 

This Introductory Python class is designed for computer-literate people with no programming background who wish to learn basic Python programming. The course is aimed at those who want to learn “data wrangling” – manipulating downloaded files to make them amenable to analysis. We concentrate on language basics such as list and string manipulation, control structures, simple data analysis packages, and introduce modules for downloading data from the web.

Details

 


Goals

 

This Introductory Python class runs over four weeks, with five hours of class per week (split into 2 ½ hour evening classes). Classes will be given in a lab setting, with student exercises mixed with lectures. Students should bring a laptop to class. There will be a modest amount of homework after each class. Due to the focused nature of this course, there will be no individual class projects but the instructors will be available to help students who are applying Python to their own work outside of class.

Certificate

Certificates are awarded at the end of the program at the satisfactory completion of the course.

Students are evaluated on a pass/fail basis for their performance on the required homework and final project (where applicable). Students who complete 80% of the homework and attend a minimum of 85% of all classes are eligible for the certificate of completion.


Syllabus

Unit 1: List manipulation

  • Simple values and expressions
  • Defining functions, using ordinary syntax and lambda syntax
  • Lists
    • Built-in functions and subscripting
    • Nested lists
  • Functional operators: map and filter
  • List Comprehensions
  • Multiple-list operations: map and zip
  • Functional operators: reduce

Unit 2: Strings and simple I/O

  • Characters
  • Strings as lists of characters
  • Built-in string operations
  • Input files as lists of strings
  • Print statement
  • Reading data from the web
    • Using the requests package
    • String-based web scraping (e.g. handling csv files)

Unit 3: Control structures

  • Statements vs. expressions
  • For loops
    • Variables in for loops
  • if statements
    • Simple and nested if statements
    • Conditional expressions in lambda functions
  • While loops
    • break and continue

Unit 4: Data Analysis Packages

  • NumPy
    • Ndarray
    • Subscripting and slicing
    • Operations
  • Pandas
    • Data Structure
    • Data Manipulation
    • Grouping and Aggregation

Preparation – How to set up Python environment

[IMPORTANT] In the class we will use Python 3. If you are following this video to set up Python environment, please make sure you download the Python 3.X version starting from 1 min 23 s in the video.

Reviews

There are no reviews yet.

Date and Time

April Session

Apr 20 - May 13, 2020, 7:00-9:30pm
This class is held on Mondays and Wednesdays
Day 1: April 20, 2020
Day 2: April 22, 2020
Day 3: April 27, 2020
Day 4: April 29, 2020
Day 5: May 4, 2020
Day 6: May 6, 2020
Day 7: May 11, 2020
Day 8: May 13, 2020
$1590.00
Enroll Now

June Session Early-bird Pricing!

Jun 2 - Jun 25, 2020, 7:00-9:30pm
This class is held on Tuesdays and Thursdays
Day 1: June 2, 2020
Day 2: June 4, 2020
Day 3: June 9, 2020
Day 4: June 11, 2020
Day 5: June 16, 2020
Day 6: June 18, 2020
Day 7: June 23, 2020
Day 8: June 25, 2020
$1590.00$1510.50
Register before May 3rd to take advantage of this price!
Enroll Now