��������

This course is designed for professionals seeking to enhance their workplace efficiency and creative capabilities by leveraging the power of Artificial Intelligence. Students will gain hands-on experience with leading AI tools integrated into common business applications like Microsoft 365 and Google Workspace, as well as standalone platforms for automation, data analysis, and creative content generation. The curriculum focuses on practical, real-world applications, moving from foundational concepts of AI and prompt engineering to advanced skills in automating workflows, analyzing data, and developing client-facing solutions. Through a series of practical labs and a final capstone project, learners will build a portfolio of AI-driven work, equipping them with immediately transferable skills.

No prior AI knowledge is required. However, successful students should have:

• General Computer Proficiency: Comfort with navigating a computer, using a web browser, and managing files.

• Basic Office Software Skills: Prior experience using a word processor (e.g., MS Word, Google Docs) and a spreadsheet program (e.g., MS Excel, Google Sheets).

• A Willingness to Explore: An eagerness to learn and experiment with new digital tools.

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

1. Generate Professional Content: Utilize AI writing assistants to draft, summarize, and refine business communications, reports, and marketing materials.
2. Automate Repetitive Tasks: Design and implement multi-step automated workflows that connect common business applications to save time and reduce errors.
3. Analyze Business Data: Employ AI-driven tools within spreadsheets and business intelligence platforms to identify trends, create visualizations, and derive actionable insights from data
4. Enhance Creative Presentations: Use AI tools to design visually compelling presentations and generate custom images and video for professional use.
5. Apply AI Ethically: Evaluate the ethical implications of using AI in the workplace, including data privacy, potential for bias, and responsible implementation.

AI productivity refers to the use of artificial intelligence (AI) to enhance efficiency and effectiveness in various tasks and processes across industries.

This can include automating routine tasks, analyzing data quickly, optimizing workflows and providing insights that help in decision-making through the integration of AI tools. New technology advancements, like generative AI are changing the landscape for AI and its role in the workplace and overall productivity gains.

The potential for AI is still highly anticipated as up to 300 million full-time jobs have the potential to be replaced by these new technologies, according to a report from Goldman Sachs.

For individuals and organizations, AI tools can streamline operations, reduce errors, and free up team members time for more strategic activities. Examples of AI features include the use of AI for project management, customer service automation, data analysis and original content creation. Generative pretrained transformer (GPT) is a chatbot that uses AI and is built around large language models (LLMs). They are also an increasingly important application of machine learning (ML).

The goal of AI productivity is to improve output and outcomes while minimizing resource expenditure and ultimately boosting the user experience. A study conducted by the National Bureau of Economic Research backs this, finding that access to AI assistance like GPT increased productivity of customer support agents by 14%.

The introduction of AI productivity tools in the rapidly evolving world has changed how businesses are run and how people perform everyday tasks. The AI movement isn’t just about getting things done faster, it’s about being smarter and working more efficiently. What makes up most AI productivity are AI productivity tools, which are software applications that use AI to help individuals and businesses complete tasks. These AI productivity tools come in web-based and in app form. By using machine learning and natural language processing to do things like automating citations, working from prebuilt templates and writing code.

These types of software applications range in uses and complexity. Some are smart assistants that can sort through emails in just a few clicks. While other solutions use algorithms and metrics to predict the code that needs to be written or give tips to complete tasks. Some of the most popular tools used in business today are as follows.

1. Grammarly
2. Notion
3. ChatGPT
4. Claude
5. Asana
6. Otter.ai
7. watsonx Assistant
8. watsonx Orchestrate
9. Midjourney
10. watsonx Code Assistant
11. Microsoft Copilot

Grammarly is an AI cloud-based writing assistant that is used for grammar optimization, punctuation, spelling, among other writing aspects. The tool can be used for anyone looking to improve copywriting, long-form writing or general everyday writing.

Notion, similar to Grammarly, is a writing and note-taking tool that recently introduced its AI version. Notion AI is a collection of AI-powered tools that can autofill summaries, answer questions, and translate words into multiple languages.

ChatGPT was created by OpenAI, based on GPT-4 architecture and is trained on large amounts of text data to assist in writing essays, answering questions, critiquing writing and more. The premium version of ChatGPT can even do image generation and voice inputs.

Claude is another AI assistant that can summarize meetings, answer questions, and write code. It’s powered by LLMs and is another popular productivity app used by individuals today to assist in writing social media posts, such as Linkedin posts or Instagram captions.

Asana is a project management tool that helps organizations manage tasks and can integrate with multiple apps, such as Microsoft teams, Gmail, iOS and Outlook. Asana AI uses AI to automate tasks and create summaries, saving teams time and money.

Otter.ai is a transcription tool that summarizes recorded calls and helps users transcribe conversations from speech to text in real time.

Watsonx Assistant™ is a conversational AI solution that empowers employees within an organization to build AI agents and AI chatbots. The tool can be integrated with multiple apps and designed for nontechnical builders.

IBM® watsonx Orchestrate™ is a generative AI and automation solution that can automate tasks and simplify complex processes. The tool offers prebuilt apps, skills and assistants to help members of an organization perform tasks.

Midjourney is an AI-image generation tool that creates visuals from text prompts. It’s used by artists and designers to assist in creating unique work.

watsonx™ Code Assistant™ uses gen AI to generate net new code and translate code from one language to another or refactor legacy code. The tool helps developers and IT operators speed up application modernization efforts.

Microsoft Copilot is an AI-powered tool that uses LLMs and the organization’s data to help users with productivity and creativity. Copilot can suggest new ideas and automate tasks, such as email writing and summarization.

AI productivity tools that are revolutionizing the approach to tasks from brainstorming to customer support. These major shifts in technology are enabling teams to generate ideas and resolve issues more efficiently. By using advanced algorithms, these tools help reduce the perplexity often associated with complex decision-making processes, allowing for clearer insights and better outcomes.

The integration of AI into everyday workflows can significantly boost productivity, transforming how individuals and team members collaborate. Some key benefits include:

1. Enhanced time savings
2. Increased efficiency 
3. Enhanced decision-making 
4. Improved accuracy 
5. Better personalization
6. More scalability

Enhanced time savings

AI can automate repetitive tasks, freeing up time for employees to focus on more strategic initiative and creative brainstorming. An example comes from the 2023 Forrester Consulting Total Economic Impact study, which found a 30% reduction in interaction handle time for chatbot-augmented service agents with IBM Watson Assistant. The improvement is valued at USD 2.4 million over a three-year period, according to the study.

Increased efficiency

The AI tools streamline workflows, allowing teams to manage projects and tasks more effectively, which leads to quicker project completion. Separately, the added efficiency and reduction of errors can lead to significant cost savings over time, allowing for more effective resource allocation. An example of efficiency is IBM watsonx Orchestrate, specifically within the procurement world. watsonx Orchestrate uses several solutions for procurement, including Ask Procurement, contract management and procure to pay and order management.

Enhanced decision-making

AI analyzes large datasets, providing insights that help organizations make informed decisions based on real-time information. It can also enhance communication among team members, fostering a more collaborative environment that encourages idea sharing and teamwork. The watsonx Orchestrate solution is also an example of improved decision-making. With the watsonx Orchestrate capabilities, teams can automate tasks and simplify complex processes, which will save teams time and resources.

Improved accuracy

AI tools can minimize human error in data entry and content generation and help ensure higher-quality outputs. The technology can reduce the need for revisions and foster more efficient task management. watsonx Code Assistant and the IBM Chief Information Officer (CIO) organization is a great example of what accuracy can do. With watsonx Code Assistant for Red Hat Ansible Lightspeed, 60% of Ansible Playbook content was automatically generated by watsonx Code Assistant.

Better personalization

Many of the AI tools on the market, including generative AI tools, harness advanced technology to adapt to individual preferences, offering customized recommendations that improve the user experience. ChatGPT is a good example of personalization as it recently included a personalization feature, aimed at preventing users from having to repeat common instructions from one task to another.

More scalability

AI solutions can adapt and grow with an organization, accommodating increased workloads while maintaining high productivity levels and mitigating time-consuming tasks. An example of a tool that is highly scalable is Notion AI. The solution has seen such data growth that they expanded their database infrastructure to a more complex sharded architecture. The solution “maintained a total of 480 logical shards while helping ensure long-term scalable data management and retrieval capabilities,” said Notion in a post on its website.

A comprehensive course e-book, lab manual, and AI-generated video lectures will be provided via the learning platform. No software purchases are required. Students will use the free versions of the following tools:

• Core AI Assistants: Microsoft Copilot, Google Gemini
• Productivity Suites: Google Workspace or Microsoft 365 Online
• Data & BI Platforms: Microsoft Power BI Desktop, Google Looker Studio
• Automation Platforms: Zapier, Microsoft Power Automate
• Creative AI Tools: Microsoft Designer, HeyGen
• Chatbot Platforms: Tidio, Voiceflow

Fall 2025: 

September 18 - December 4, 2025 | Thursdays | 6:00 - 8:00 pm 

Synchronous/Live Online Sessions: 10; Asynchronous/Self-Paced Sessions: 10; Total Sessions: 20; BLENDED ONLINE*

*This course is delivered in a hybrid format, which blends live, scheduled online sessions with flexible, self-paced learning. Live classes will be held synchronously via Zoom on the dates specified in the schedule below for real-time lectures, discussions, and workshops. On other weeks, you will complete assignments and learning modules asynchronously (on your own time) via the course management system. This model combines the benefits of direct interaction with the instructor and peers with the flexibility to learn at your own pace.

$500 + $25 registration fee

Total: $525*

*CCNY students, staff, and Alumni Association members are eligible for a 10%  discount!

Carlos J. Garcia

Professor Garcia brings a wealth of experience in AI and machine learning with a solid foundation in cybersecurity, networking, and law enforcement education.

With a Master of Science in Information Assurance from Eastern Michigan University and numerous certifications in IT and public safety, Professor Garcia has been at the forefront of cybersecurity and digital forensics education. He played a pivotal role in initiating the cybersecurity curriculum for high schools in Michigan, significantly shaping the state's approach to cybersecurity education. As a tenure-track Assistant Professor at SUNY Westchester Community College and an adjunct professor at Eastern Michigan University, he has developed and administered a wide range of curriculum materials across various teaching platforms, from traditional classrooms to asynchronous online courses. At Eastern Michigan University, he has taught through the master's level, contributing to the development of courses in Information Assurance.

Known for his dynamic presentations and deep industry knowledge, Professor Garcia has guided numerous learners through complex IT topics and practical applications in both educational and industry settings. He was also a co-chair for the National Initiative for Cybersecurity Education (NICE) committee at NIST, where he contributed to shaping national strategies on cybersecurity education, training, and workforce development. His leadership extends into national cybersecurity defense competitions and significant contributions to community and professional educational initiatives, making him a distinguished figure in the fields of AI, cybersecurity, and public safety education.