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Python Machine Learning (Self-Paced)

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Build the fundamentals of machine learning with our self-paced Python Machine Learning Course. Learn to create predictive models, study data, and apply powerful algorithms like decision trees and random forests, no advanced math required.

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Python for Data Science (Self-Paced)

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Kickstart your data science journey with our self-paced Python for Data Science course! Learn Python fundamentals, analyze data with Pandas and NumPy, and create stunning visualizations—all while building a strong foundation for machine learning.

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Automate repetitive tasks and extract data from websites using Python in this beginner-friendly, self-paced course. Build real-world automation scripts, learn large-scale data scraping techniques, and develop the skills to run your code efficiently and independently. A strong foundation for anyone looking to streamline workflows or move into web development.

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Python Machine Learning Advanced

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Take your machine learning expertise to the next level in this comprehensive, hands-on course designed to transform foundational ML knowledge into practical, real-world applications. Move beyond standard Jupyter notebooks and explore how professional ML engineers build and deploy machine learning...

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$1,895

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Python Programming Bootcamp

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Build a confident Python foundation through guided lessons and applied exercises. You'll level up your coding skills and assemble a portfolio of polished projects that demonstrates real ability to potential employers.

(452) All levels 18 and older
$1,495

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Introductory Python

Learn the fundamentals of Python programming in this introductory course at NYC Data Science Academy. Gain the skills to manipulate data and perform basic analysis using Python, with topics such as list and string manipulation, control structures, and data analysis packages. This course is designed for computer-literate individuals with no programming background.

  • Beginner
  • 18 and older
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  • Online
  • 22 hours over 11 sessions

Start Dates (0) $1,590/person

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Class Description

Description

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.

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. 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.

Required Materials

Students should bring a laptop to class.

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

Remote Learning

This course is available for "remote" learning and will be available to anyone with access to an internet device with a microphone (this includes most models of computers, tablets). Classes will take place with a "Live" instructor at the date/times listed below.

Upon registration, the instructor will send along additional information about how to log-on and participate in the class.

School Notes: We offer a certification licensed by the NYS Board of Education.

Refund Policy

Any student wishing to withdraw from a program must notify CourseHorse in writing. The date of withdrawal for refund purposes is the last date of physical attendance. The failure of a student to notify us in writing of withdrawal may delay refund of tuition due pursuant to Section 5001 and 5002 of the Education Law.

Any student requesting cancellation within seven days after signing the Enrollment Agreement but before instruction begins will be refunded all money paid less 5% cancellation fee. Thereafter, in the event of cancellation or termination by the school, refunds will be prorated based on the student's last date of attendance.

Reviews of Classes at NYC Data Science Academy (31)

(4.4-star rating across 31 reviews)

This class: 4.0 out of 5 from 1 review

  • Introductory Python

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NYC Data Science Academy

NYC Data Science Academy offers hands-on projects and real-world applications to teach students the skills needed for a career in data science. By enrolling, students become part of a supportive network that includes the NYC Open Data Meetup.

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