Contact Information

Instructor: Dr. Olga Lepsky
Office Location: 422 (Presidential building fourth floor), entrance through 436 faculty suite
Office Hours: MW: 9-9:30am, 2-3pm
TTh: 9-9:30am, 11am-12:30pm, 2-3pm, Friday 9:00am - 1:00pm
Phone: 617-405-5930
Email: olepsky@quinccollege.edu

Photo of Professor Lepsky

I have been working as a data scientist, algorithm developer, and a lecturer in Math/CS/data science.
Technical skills: extensive working knowledge of algorithms and data structures, data science, machine learning (ML), statistics, software development in Python, Java, C++, database querying in SQL, data visualization via Tableau, text mining and natural language programming (NLP).
Communication skills: extensive experience of presentations, explaining concepts in data science, computer science, algorithms, and mathematics to technical and non-technical audience, successful interaction and problem solving with various teams like Marketing, Finance, Training, and customers.
I am interested in applying data science to improving people's live in various areas: education, healthcare, mental health, finance, data journalism. My language skills: English (fluent), Russian (fluent), Hebrew (conversational).

Course Description

Course Description:

This course allows students to explore the latest technologies by focusing on a particular contemporary topic of computer science. The topics may differ each time the course is offered. Each semester will cover a single topic. Potential areas of focus include advanced programming, game development, databases, networking and cloud computing, computer security and cryptography, robotics, natural language processing, and machine learning.

Natural Language Processing is a subfield of AI, that enables computers to understand and communicate with a human language. In this course the students will learn to use the cutting-edge technology and Python programming language and libraries to identify the topic of a text, check sentiment of tweets and reviews, build a "fake news" detector, and a chatbot.

Course Learning Outcomes

Upon successful completion of this course, you will be able to:

Compare and contrast current or emerging technology with historic approaches. (CLO:1)
Design and implement a solution utilizing the technology introduced in this course. (CLO:2)
Evaluate the effectiveness of the technology introduced in this course. (CLO:3)
Examine how this technology has influenced industry, individuals, and society. (CLO:4)

(CLO = Course Learning Outcome)

Course Materials

Third-party Software:

Datacamp
Datacamp is an interactive online learning platform designed to teach data science, machine learning, and programming through hands-on exercises and real-world projects. With a focus on practical skills, Datacamp offers an extensive library of courses, including tutorials on Python, natural language processing, and artificial intelligence. For this course, you will use Datacamp to access targeted lessons, practice coding skills, and complete exercises related to text analysis, sentiment detection, and chatbot development. Its engaging, self-paced environment allows learners to build confidence and apply concepts directly in Python.

During this course, you might have the opportunity to use public online services and/or software applications sometimes called third-party software such as a blog or wiki. While some of these could be required assignments, you should not provide personal information about yourself or your classmates on a public site. Where appropriate, you may use a pseudonym or nickname. Some written assignments posted publicly may require personal reflection/comments, but the assignments will not require you to disclose any personal information. If you have any concerns about this process, please contact your instructor.

Course Syllabus

Course Syllabus

Academic Integrity

Please read and familiarize yourself with the following Quincy College academic integrity policies:

Accessibility & Privacy Policies

Various tools and technologies will be utilized throughout this course. For information on the privacy and accessibility standards of specific technologies, please refer to the following policies:

Instructure (Canvas) Privacy
Instructure (Canvas) Accessibility
Zoom Privacy
Zoom Accessibility
Turnitin Privacy
Turnitin Accessibility
Respondus Privacy
Repondus (LockDown Browser) Accessibility
YouTube Privacy
Google (YouTube) Accessibility
Datacamp Privacy
Datacamp Accessibility

QC Student Accessibility Services (SAS) provides academic support, accommodations, and many other services to meet student accessibility needs. For further information, or if you feel you require support, please contact Student Accessibility Services.

QC Student Success

Need Help?

Free support services are available for QC's students. You can access resources and assistance through QC's Student Services.

Next Steps: Begin This Course

Complete the following:

Review the material in the Start Here module.
Complete the "About you" survey.
Participate in the Course introductions discussion board.

Click the Next ▶ button to continue.