columbia university artificial intelligence free online course

This is the best place to follow Artificial Intelligence online course completely free providing Columbia University AI course this course will help you for better understanding of artificial intelligence and its field coverage.

Artificial Intelligence (AI) is the new “big thing” on the block. Almost every large company has a dedicated AI team, and countless startups base their entire product/service offerings around AI. And if you’ve read the latest blog posts or tweets on this subject matter, then you’ll know it’s only a matter of time before AI starts ruling over humans in one way or another. In other words, this buzz is not going away anytime soon; in fact, the train is just about to leave the station. So if you want to board this train and become an expert in the field of AI, but don’t want to waste hours (or even weeks?) reading yet another book that might turn out to be average at best, then let me present you with a more digestible alternative: online courses.  All the courses I provide links to are available online and are free of charge, which means they won’t cost you any money whatsoever. These courses have been taught by actual experts from institutions like Stanford University or Columbia University .

The Online AI program from Columbia Engineering

Drive transformational change for your organization by building systems, products, and services powered by artificial intelligence.

Amplify Your Technological Expertise

Columbia Engineering, top ranked for engineering and artificial intelligence2, is where visionaries come to confront the grand challenges of our time and design for the future.

AI is transforming our world, and our online AI program enables business leaders across industries to be pioneers of this transformation.

For online graduate engineering programs1

6 courses

1 bridge course

1 in-person immersion

9–18 months to complete

Lead at the Forefront of AI Technology

Acquire cutting-edge AI skills from some of the most accomplished experts in computer science and machine learning. Learn more about our online AI program.Request Information 

Scholarships Available for April 2022 Cohort

Qualified applicants are eligible for a scholarship to our online AI program. Get in touch and take the first step to amplifying your expertise with some of the most accomplished minds in the field.

Intensive Curriculum. Cross-Industry Connections.

Discuss emerging research and trends with our top faculty and instructors, collaborate with your peers across industries, and take your mathematical and engineering skills and proficiency to the next level.

Rigorous Curriculum
From the self-paced bridge course to the core courses — Intro to AI and Business for AI; Algorithms and ML; Neural Networks and DL; NLP and Speech; Computer Vision and Robotics; and Security, Privacy, Policy — the curriculum is designed to build on your knowledge and expand it.

Explore our curriculumExternal link:open_in_new

Expert Columbia Faculty
This program was developed by some of the brightest minds working today, who have significantly contributed to their respective fields. Our faculty and instructors are the vital links between world-leading research and your role in the growth of your industry.

Explore our facultyExternal link:open_in_new

In-Person NYC Immersion
During the program, you will take part in a three-day immersion experience in New York City, a buzzing tech hub, featuring working sessions, presentations, networking opportunities, and community-building events with your peers, instructors, and alumni.

Explore our in-person immersionExternal link:open_in_new

AI Learning in the Digital Campus

DASHBOARD

Get one-click access to upcoming assignments, live classes, grades, contacts, and tech support.

MOBILE APP

Complete coursework, attend live classes, access your dashboard, and work in offline mode.

COURSEWORK

Optimize your learning through dark mode, searchable video transcripts, variable video speeds, closed captioning, and more.

LIVE CLASSES

Dive in with small-group breakout rooms, streaming HD video and audio, real-time presentations and annotations, and more.

Learn more about the online AI learning experience at Columbia Engineering.

Join the Next Generation of AI Pioneers at Columbia Engineering

Request Information 


Admissions Overview

Columbia Engineering seeks innovative tech professionals and business leaders from diverse industries eager to amplify their technological expertise and apply it across verticals.

All applicants must have programming experience. Knowledge of Python, Java, C, or C++ preferred.

To be considered for admission in the non-credit executive education program, you must submit:

  • The online application.
  • College Transcripts.
  • Résumé or CV.
  • Personal/Professional statement (500 words).
  • Application fee of $85 (waivers available).

See all admissions deadlines and detailed application requirementsExternal link:open_in_new.

We offer multiple start dates per year with rolling admissions. See the deadlines for the April 2022 cohort. Scholarships available.

Priority deadline:

January 31, 2022

Final deadline:

February 28, 2022

The Revolutionizing Potential of AI

The strategic use of artificial intelligence is already transforming lives and advancing growth in nearly every industry, from health care to education to cybersecurity.

Jobs in AI are proving immune to traditional market adjustments. Because they are still emerging professions, skill shortages are more acute, and business leaders consistently cite difficulties when hiring for data analysts and scientists, AI and machine learning specialists, and software and application developers, among others3. The Bureau of Labor Statistics also projects that employment in computer and information technology occupations will grow by 11% between 2019 and 2029.4

Projected Job Growth in Computer
and IT Professions by 2029

1 U.S. Best Online Master’s in Engineering Programs ranked in 2021 by U.S. News & World Report (Accessed July 2021) https://www.usnews.com/education/online-education/engineering/rankings;arrow_upwardReturn to footnote reference
2 U.S. Best Artificial Intelligence Programs, ranked #12 in 2018 by U.S. News & World Report (Accessed July 2021) https://www.usnews.com/best-graduate-schools/top-science-schools/artificial-intelligence-rankings;arrow_upwardReturn to footnote reference
3 U.S. Bureau of Labor Statistics, Occupational Outlook HandbookComputer and Information Technology OccupationsExternal link:open_in_new (accessed January 2021) arrow_upwardReturn to footnote reference
4 2020 Workplace Learning Report (page 35) by LinkedIn LearningExternal link:open_in_new arrow_upward

Admissions

At Columbia Engineering, the Fu Foundation School of Engineering and Applied Science, we cultivate an environment that embraces interdisciplinary thought, creativity, and social responsibility.

The online Columbia Artificial Intelligence (AI) program is designed for professionals and leaders with programming experience who are seeking non-credit executive education to advance their skills. We welcome applications from curious and innovative thinkers across industries who can translate AI tools and technologies into solutions that create efficiencies and advance humanity.

Application Deadlines

The program has multiple start dates per year, so you have the flexibility to choose the one that best suits your schedule. You can complete the program in 9 to 18 months while continuing to work.

For each cohort, we offer a priority application deadline to help you plan. The application fee is waived for all applications received by the priority deadline.

CohortPriority DeadlineFinal Deadline
April 2022January 31, 2022February 28, 2022

Admissions Criteria

To be eligible for the program, you will need to meet the following criteria:

  • Bachelor’s degree required; major in computer science, engineering, or a related field preferred
  • Python experience   
  • Java, C, or C++ experience
  • Work experience in a field that requires programming skills, including software engineering, software development, data science, data manipulation, and data analysis

At least five years of work experience is preferred. Learners entering the AI program should have taken undergraduate courses in statistics, linear algebra, and multivariable calculus to be able to answer these prerequisite questionsExternal link:open_in_new. Applicants may need to review their undergraduate coursework prior to applying.

Application Requirements

Applicants are required to submit the following materials to be considered for admission:

Online Application

Begin your application now.External link:open_in_new

Résumé

On your résumé or CV, be sure to clearly and briefly outline relevant employment held (including titles of jobs and start/end dates), and include the following where appropriate: 

  • Research activities
  • Academic honors, including fellowships you have been awarded
  • Honorary societies
  • Awards for service or leadership you have received
  • Publications

Transcripts

We require that you have all colleges and universities you previously attended send official transcripts to Columbia University. You may submit unofficial transcripts and web printouts with your application, but official transcripts will need to be provided before registering for your term. Transcripts can be submitted electronically to [email protected] or sent by mail to:

Columbia University
Executive Education Program Processing
Columbia Artificial Intelligence (AI) program
P.O. Box 30096 028-001
College Station, TX 77842

If you are an international applicant, and the institution(s) you attended do not issue transcripts in English, you will need to submit translations of your transcripts and degree/diploma certificates. The translations must be conducted by a reputable service provider. English proficiency is required for all applicants.

International applicants can submit unofficial transcripts as part of their application and do not need to submit their transcript through the evaluation process unless they have been admitted into the program. 

Personal/Professional Statement

The personal/professional statement serves as an opportunity to discuss what you hope to gain from the program and why this program is a good path to achieving your goals.

The length is flexible, but you should aim to write between 350-500 words and use the space needed to address the following:

  • What are your post-completion plans or career goals?
  • How will this program help you accomplish your goals?
  • What do you hope to gain from this program?

If there are any special circumstances that need to be brought to the attention of the Enrollment Committee, please include that information in your response.

Application Fee

There is a nonrefundable application fee of $85. Fee waivers are available for Columbia University alumni, certificate recipients of Columbia Engineering Boot Camps, active-duty military and veterans, and those who apply by the priority deadline of their desired cohort start date. 

Immersion Requirements for International Learners

The online Columbia AI program requires all learners to travel to the Columbia University campus in New York for a long weekend to attend the in-person immersion. This non-degree program is not eligible for a student visa, and individuals are not permitted to study in visitor or visa waiver (ESTA) status. Therefore, international applicants are expected to have their own immigration status that permits them to live in or enter the United States.

If you have any questions about visa requirements, please email the International Student and Scholar Office at [email protected].

Online AI Curriculum

The AI certificate’s curriculum strives to enable discussion of emerging AI research and trends with world-class Columbia faculty and instructors, facilitate valuable cross-industry collaboration among peers, and help technical leaders integrate AI into their organization’s strategic planning decisions.

This non-credit, non-degree executive education program is composed of 1 self-paced bridge course, 6 core courses with live and asynchronous coursework, and an essential immersion experience at Columbia University’s Morningside campus in Manhattan. You may choose to complete the program full time (2 courses per term) or part time (1 course per term).

A state-of-the-art digital learning platform brings the curriculum to life through one-click access, live classes, offline learning, robust search and collaboration capabilities, and tech support.

6 courses

1 bridge course

1 in-person immersion

9–18 months to completeRequest Information 

Bridge Course

Technical Foundations

This self-paced asynchronous course is strongly recommended for all learners to help them ensure a solid knowledge base before beginning the online AI program. The syllabus covers statistics, linear algebra, multivariable calculus, probability, data structures, basic programming in Python, and foundational topics in math that are relevant to the content in the core courses.

You should expect to review the mathematical and technical coursework as well as complete the self-assessment. The content from the bridge course will be available for the duration of the program so that you can refresh your understanding of these topics at any time.

By the end of the bridge course, learners will be able to:

  • Write Python scripts and programs that process, clean, manipulate, and visualize data as needed for AI applications.
  • Understand and use functions in Python, including the scope of parameters and variables.
  • Explain and interpret mathematical concepts that are foundational to AI algorithms and approaches.
  • Build programs that use object-oriented programming concepts to inform their design.
  • Use Pandas DataFrames and functions to analyze datasets and aggregate data.
  • Create visualizations using Matplotlib.

Core Courses

The core of the curriculum is designed around knowledge-building through world-class instruction, thought-provoking discussion, and peer collaboration. To help learners reinforce their knowledge, and to measure each participant’s progress, instructors use a variety of assessments, including diagnostic quizzes, as well as programming, coding, and data structures exercises, and final projects.

Intro to AI and Business for AI

Learn AI fundamentals and key ideas behind the design of intelligent agents for real-world problems, including search, games, machine learning, and constraint satisfaction. Gain exposure to applications of AI and machine learning in business—such as customer service, sales, and marketing—and study how AI is used in other industries like retail, finance, health care, and manufacturing.

By the end of this course, learners will be able to:

  • Communicate efficiently with business stakeholders, IT specialists, and data analysts on how to create an AI solution.
  • Articulate the process of constructing sentiment engine and facial recognition systems.
  • Show a strong awareness of challenges as well as of ethical and policy issues businesses may face while developing AI solutions.
  • Discuss ongoing research into the ethics of AI, including explainable AI (XAI), correcting bias in data, and inclusive AI.
  • Describe strategies for modifying a chatbox to improve customer experience.
  • Understand potential challenges in building an AI system for customer service.
  • Compile and evaluate an AI team.

Algorithms and Machine Learning

Learn fundamental ideas of design and analysis of efficient algorithms, including sorting and searching, graph algorithms, and dynamic programming. After going over general algorithmic approaches, focus on supervised learning techniques for regression and classification on real-world datasets.

By the end of this course, learners will be able to:

  • Recognize problems for which machine learning may be suitable.
  • Analyze algorithms to determine and verify which are more effective than others.
  • Discuss fundamental ideas of design and analysis of efficient algorithms, including sorting and searching, graph algorithms, and dynamic programming.
  • Focus on supervised learning techniques for regression and classification on real-world datasets.

Neural Networks and Deep Learning

Study the nature of deep learning (DL) and neural networks, explore applications for both, and identify ways in which DL and neural networks can be applied to solve industry or business problems.

By the end of this course, learners will be able to:

  • Know the theoretical underpinnings as well as the architecture, performance, datasets, and applications of neural networks and deep learning.
  • Become familiar with TensorFlow deep learning framework and the Google Cloud computational platform, with graphics processing units (GPUs).

Natural Language Processing and Speech

Learn the fundamental approaches to language modeling, and discuss applications such as machine translation, text generation, information extraction, and automatic summarization.

By the end of this course, learners will be able to:

  • Use machine learning methods for language modeling, part of speech tagging, and parsing.
  • Consider applications such as information extraction, machine translation, text generation, and automatic summarization.
  • Examine state-of-the-art neural network approaches to natural language processing.
  • Understand how tobuild automated systems that can analyze, understand, and produce language using industry standard tools like PyTorch and Hugging Face.

Computer Vision and Robotics

Computer vision forms the basis of the perception problem, while robots interact with the physical world via mechanisms. Examine how algorithms and learning integrate with physical systems. Cover ideas in image sensing, processing and filtering, segmentation, and object recognition. Perform planning and estimation for robotic systems.

Security, Privacy, Policy

Learn fundamental aspects of data security and privacy, explore how these play into technical tasks like data mining and storage, and examine the legal and social frameworks surrounding these issues. Study how all relate to policy development and solutions.

Course titles and content in the online AI executive education program are subject to change.

On-Campus Immersion Experience

A cornerstone of the online AI program, this three-day, in-person immersion is an invigorating experience in New York City, a hub of innovation, creativity, and research.

Set to take place on Columbia’s Morningside campus in Manhattan, the immersion features working sessions, presentations, networking opportunities, and community-building events with peers, instructors, and alumni.

The first immersion is planned for September 2022. The dates for this in-person event will be shared in the coming months as we continue to get updates on public health and university guidance for large group meetings.  If public health guidance warrants it, the event may be delivered virtually.

International Visas

The online AI program from Columbia Engineering is a non-degree program. It does not grant eligibility for a student visa, and individuals are not permitted to study on visitor or visa waiver (ESTA) status. Therefore, international applicants wishing to attend the in-person NYC campus immersion are expected to have their own immigration status that permits them to live in or enter the United States, in accordance with the U.S. Department of State guidance. If you have any questions about visa requirements, please email the International Student and Scholar Office. You may also visit the U.S. Department of State VisaExternal link:open_in_new Information website for more information regarding visiting the U.S.

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