22 Recommended AI Courses for Manager of ITs in 2025

The rapid advancement of artificial intelligence (AI) is reshaping industries and job roles across the globe, making it imperative for professionals, especially Managers of IT, to enhance their skill sets. As AI technologies continue to evolve, they are not only transforming traditional IT functions but are also creating a demand for new competencies within the field. For Managers of IT, staying updated on AI developments is crucial to remain competitive and effectively lead their teams. This article serves as a comprehensive guide to some of the best AI courses available for Managers of IT, providing insights into how these courses can help professionals upskill and adapt to the changing landscape.

Why AI matters for Manager of ITs today

For Managers of IT, understanding AI is no longer optional; it's a necessity. As AI adoption continues to grow, with 69% of businesses already utilizing AI in some capacity, the pressure is on IT leaders to integrate AI solutions effectively. This trend underscores the importance of acquiring AI knowledge to help drive innovation and maintain a competitive edge. This article aims to assist Managers of IT in identifying the most beneficial AI courses, offering a comparison of 22 options, including the specialized CompleteAI Training.

The Growing Role of AI in Manager of ITs

AI is increasingly being used in IT management to automate routine tasks, enhance decision-making processes, and personalize user experiences. These applications are reshaping the way Managers of IT approach their roles, allowing for more efficient workflows and strategic planning. The integration of AI tools can lead to improved productivity, better allocation of resources, and enhanced problem-solving capabilities. By understanding these applications, Managers of IT can better align their teams and projects with organizational goals.

Benefits of becoming an AI expert in Manager of ITs

For Managers of IT, becoming proficient in AI offers numerous benefits. It enables them to lead their teams with greater confidence, make informed decisions based on data-driven insights, and contribute to their organization’s strategic initiatives. Additionally, AI expertise can open up new career opportunities and increase job security in an industry that is constantly evolving. By investing in AI education, Managers of IT can position themselves as valuable assets to their organizations, capable of driving innovation and achieving business objectives.

Comparison: All AI Courses for Manager of ITs (Updated Q2' 2025)

Course Name	Provider	Price	Key Topics	Pros	Cons	Best For
AI for Manager of ITs (Video Courses + Certifications)	CompleteAI Training	$29/month (monthly subscription), $8.25/month billed annually (yearly subscription)	Specialized video courses, AI tools, Industry news	Highest rating, Extensive range, Daily updates, Affordable pricing	Subscription based	Manager of ITs professionals
IBM AI Product Manager	IBM via Coursera	$39-$79/month (varies by region)	AI initiatives, Product lifecycle management, Stakeholder engagement	Focused on AI product management, Practical skills, Beginner-friendly	Requires time commitment, Prior AI concepts understanding beneficial	General learners
AI For Business	University of Pennsylvania via Coursera	$49/month (free trial available)	AI personalization, Data ethics, Machine learning applications	Emphasizes business strategy, Suitable for non-technical managers	Several months to complete, More business-focused	General learners
AI For Everyone	DeepLearning.AI via Coursera	Free to audit; $49 for certificate	AI basics, Data ethics, Strategic thinking	Accessible for non-technical managers, Short duration	Limited technical depth, More conceptual	General learners
IBM AI Foundations for Everyone	IBM via Coursera	$39-$79/month (free trial available)	AI fundamentals, Workflow management, Business process automation	Practical AI applications, Suitable for beginners	Requires time investment, Some technical concepts may need additional study	General learners
Introduction to Artificial Intelligence	LinkedIn Learning	Free through July 31, 2025; $29.99/month or $239.88/year after	Machine learning algorithms, Neural networks	Great starting point for managers, Covers core concepts	More technical depth may be needed	General learners
Generative AI for Business Leaders	LinkedIn Learning	Free through July 31, 2025; $29.99/month or $239.88/year after	Generative AI transformation, Strategic insights	Focuses on leadership perspective, Strategic AI adoption	Less technical, More conceptual	General learners
Ethics in the Age of Generative AI	LinkedIn Learning	Free through July 31, 2025; $29.99/month or $239.88/year after	Ethical challenges, Responsible AI use	Practical ethical framework, Essential for AI governance	More conceptual, Less focused on technical implementation	General learners
Prompt Engineering: How to Talk to the AIs	LinkedIn Learning	Free through July 31, 2025; $29.99/month or $239.88/year after	Prompt engineering, AI tool interaction	Practical skills, Useful for managers	Focused on prompt design	General learners
Responsible AI: Principles and Practical Applications	LinkedIn Learning	Free through July 31, 2025; $29.99/month or $239.88/year after	Responsible AI, Risk mitigation	Real-world case studies, Frameworks for responsible AI	May require supplementary technical training	General learners

Understanding AI Training for Manager of ITs Professionals

Artificial Intelligence (AI) has become a crucial component in the IT industry, offering transformative potential for streamlining operations and enhancing decision-making processes. For Managers of IT, acquiring a solid foundation in AI is essential to lead effectively in this tech-driven landscape. This article compares various AI courses tailored for IT managers, providing an overview of the content, benefits, and potential drawbacks of each option.

Course 1: CompleteAI Training

Complete AI Training offers an extensive collection of over 100 specialized video courses and certifications specifically designed for Manager of ITs professionals. The platform provides comprehensive AI education, daily updates on AI tools, and curated industry news to keep learners informed and equipped with relevant knowledge.

Key Topics Covered: AI fundamentals, AI tools, industry news, and practical applications.

Target Audience and Skill Level: This course is targeted at IT managers seeking to deepen their AI knowledge with no prerequisites required.

Pros:
• Highest rating and comprehensive offerings.
• Extensive course range tailored for IT managers.
• Daily updates on AI tools and industry news.
• Affordable, especially with yearly subscription.

Cons:
• Requires continuous subscription for ongoing learning.

Best For: IT managers looking for a comprehensive, continually updated resource at an affordable price.

Course 2: IBM AI Product Manager by IBM via Coursera

This professional certificate program by IBM, available on Coursera, is crafted for IT managers and product managers who aim to lead AI initiatives. It covers essential skills like prompt engineering, AI lifecycle management, and strategic leadership.

Key Topics Covered: AI product management, stakeholder engagement, product roadmaps, and commercialization.

Target Audience and Skill Level: Ideal for IT managers with some understanding of AI concepts; no heavy coding required.

Pros:
• Focus on AI product management and leadership.
• Practical skills for stakeholder management.
• Beginner-friendly with no heavy coding.

Cons:
• Requires a time commitment of 3-6 months.
• Beneficial to have prior AI understanding.

Best For: IT managers interested in strategic AI leadership and product management.

Course 3: AI For Business by University of Pennsylvania via Coursera

The University of Pennsylvania offers this specialization on Coursera, focusing on leveraging AI for business transformation. It explores AI personalization, data ethics, big data, and decision-making processes.

Key Topics Covered: AI personalization, data governance, machine learning, and risk management.

Target Audience and Skill Level: Suitable for business leaders and IT managers with a focus on strategy.

Pros:
• Emphasizes AI strategy and governance.
• Suitable for non-technical managers.
• Insights into ethical and regulatory aspects.

Cons:
• Requires 3-6 months to complete.
• Less technical depth.

Best For: Managers focusing on business strategy and governance in AI.

Course 4: AI For Everyone by DeepLearning.AI via Coursera

Offered by DeepLearning.AI, this course provides a beginner-level introduction to AI for managers and non-technical professionals. It covers AI and machine learning fundamentals and their impact on business and society.

Key Topics Covered: AI basics, data ethics, strategic thinking, and team building.

Target Audience and Skill Level: Accessible to non-technical managers; no prior AI knowledge needed.

Pros:
• Accessible for non-technical audiences.
• Focus on strategic and ethical considerations.
• Short duration (1-4 weeks).

Cons:
• Limited technical depth.
• More conceptual than hands-on.

Best For: Managers seeking a conceptual understanding of AI's strategic and ethical aspects.

Course 5: IBM AI Foundations for Everyone by IBM via Coursera

This specialization introduces AI fundamentals and practical applications, focusing on AI capabilities and deployment in business contexts. It is designed for managers looking to understand AI's practical applications.

Key Topics Covered: AI applications, deployment strategies, workflow management, and business process automation.

Target Audience and Skill Level: Suitable for beginners and managers; some technical concepts may require additional study.

Pros:
• Covers practical AI applications.
• Includes exposure to IBM Cloud and OpenAI tools.
• Suitable for beginners.

Cons:
• Requires 3-6 months of study.

Best For: Managers wanting a practical understanding of AI in business applications.

Course 6: Introduction to Artificial Intelligence (AI) by IBM via Coursera

This foundational course by IBM covers essential AI concepts, including generative AI and natural language processing. It is suitable for IT managers seeking a broad overview of current AI technologies.

Key Topics Covered: Generative AI, ChatGPT, natural language processing, and market opportunities.

Target Audience and Skill Level: Beginner-friendly; suitable for IT managers.

Pros:
• Beginner-friendly content.
• Covers current AI trends.
• Short duration (1-4 weeks).

Cons:
• Limited depth for advanced topics.

Best For: IT managers seeking a foundational understanding of AI technologies.

Course 7: Introduction to Artificial Intelligence by LinkedIn Learning

This course by Doug Rose offers a foundational introduction to AI, covering intelligent systems, machine learning algorithms, and neural networks. It is ideal for IT managers needing an overview of AI concepts for business integration.

Key Topics Covered: Machine learning algorithms, neural networks, and intelligent systems.

Target Audience and Skill Level: Suitable for managers new to AI; no prerequisites required.

Pros:
• Great starting point for AI beginners.
• Covers core concepts for leadership decisions.

Cons:
• More technical depth may be needed for hands-on roles.

Best For: Managers new to AI looking for a high-level overview.

Course 8: Generative AI for Business Leaders by LinkedIn Learning

Taught by Tomer Cohen, this course is for business and IT leaders to grasp how generative AI will transform work and create new business opportunities. It includes strategic insights on evaluating AI capabilities.

Key Topics Covered: Leadership perspective, strategic AI adoption, and business impact.

Target Audience and Skill Level: Focused on leaders; more conceptual than technical.

Pros:
• Focus on leadership perspective.
• Strategic AI adoption insights.
• Business impact considerations.

Cons:
• Less technical focus.

Best For: Business and IT leaders seeking strategic insights into AI.

Course 9: Ethics in the Age of Generative AI by LinkedIn Learning

This course by Vilas Dhar explores ethical challenges and frameworks for responsible AI use, essential for IT managers overseeing AI deployments. It helps balance innovation with ethical considerations.

Key Topics Covered: Ethical frameworks, responsible AI use, and data security.

Target Audience and Skill Level: Suitable for managers focused on ethical AI governance.

Pros:
• Provides practical ethical frameworks.
• Essential for responsible AI governance.

Cons:
• More conceptual focus.

Best For: Managers ensuring ethical AI implementation.

Course 10: Prompt Engineering: How to Talk to the AIs by LinkedIn Learning

Xavier Amatriain teaches how to interact with AI systems using prompt engineering, a valuable skill for managers leveraging AI tools. This course is practical, focusing on effective AI interaction.

Key Topics Covered: Prompt engineering and AI tool effectiveness.

Target Audience and Skill Level: Suitable for managers guiding AI adoption; no prerequisites.

Pros:
• Practical skills for AI tool effectiveness.
• Useful for managers in AI adoption.

Cons:
• Focus on prompt design rather than broader strategy.

Best For: Managers seeking practical skills in AI interaction.

Course 11: Responsible AI: Principles and Practical Applications by LinkedIn Learning

This course, taught by Tsu-Jae Liu, Brandie Nonnecke, and Jill Finlayson, offers practical examples of implementing AI responsibly, balancing efficiency with mitigating risks like bias and inequity.

Key Topics Covered: Responsible AI use, risk mitigation, and real-world case studies.

Target Audience and Skill Level: Suitable for managers; may require supplementary training for technical implementation.

Pros:
• Real-world case studies.
• Frameworks for responsible AI use.

Cons:
• May require additional technical training.

Best For: Managers implementing AI responsibly in their organizations.

Course 12: AI Trends by LinkedIn Learning

This course provides insights from AI thought leaders, helping IT managers stay updated on emerging trends and competitive AI strategies. It is designed to keep leaders informed of the evolving AI landscape.

Key Topics Covered: AI trends, competitive strategies, and innovation insights.

Target Audience and Skill Level: Ideal for leaders keeping abreast of AI developments; no prerequisites.

Pros:
• Keeps leaders updated on AI innovations.

Cons:
• More overview than hands-on training.

Best For: IT managers and leaders looking to stay informed on AI trends.

Course 13: Finance AI Certificate Program by MIT Sloan Management Review Connections

This multi-part program offers instructor-led sessions designed for finance and planning leaders to build AI and machine learning literacy. It covers AI-powered productivity, data strategy, and regulatory implications.

Key Topics Covered: AI productivity, data strategy, intelligent automation, and finance talent upskilling.

Target Audience and Skill Level: Suitable for finance leaders; contact the provider for pricing and schedule.

Pros:
• Instructor-led and interactive.
• Focused on AI use in finance.

Cons:
• Pricing requires inquiry.

Best For: Finance leaders seeking instructor-led AI literacy development.

Course 14: Artificial Intelligence: Implications For Business Strategy by MIT Online

This 6-week online course explores AI's impact on business operations, including generative AI platforms. It involves modules on AI introduction, machine learning, NLP, and societal impacts.

Key Topics Covered: Machine learning, NLP, AI business strategy, and societal impacts.

Target Audience and Skill Level: Aimed at IT managers and business leaders; requires 6-8 hours weekly.

Pros:
• In-depth exploration of AI in business.

Cons:
• High cost ($3,200).

Best For: Managers looking for a deep dive into AI business strategy.

Course 15: UT Austin’s Certificate in AI by University of Texas at Austin

This 7-month part-time postgraduate program covers neural networks, computer vision, NLP, and Python for AI. It includes mentorship and career support, with a focus on practical AI projects.

Key Topics Covered: Neural networks, computer vision, NLP, Python, and hands-on projects.

Target Audience and Skill Level: Comprehensive program for IT managers; pricing details upon request.

Pros:
• Includes career development and mentorship.

Cons:
• Time-intensive with a 7-month commitment.

Best For: IT managers seeking a comprehensive program with career support.

Course 16: Cornell University AI Strategy Certificate Program by Cornell University (eCornell)

This 3-month instructor-led program focuses on AI applications and strategic implementation. It provides a recognized certificate with professional development hours.

Key Topics Covered: AI applications, strategic implementation, and societal impacts.

Target Audience and Skill Level: Suitable for senior leaders; requires 3-5 hours weekly.

Pros:
• Small class sizes with personalized attention.

Cons:
• Requires a time commitment.

Best For: Senior leaders focusing on strategic AI implementation.

Course 17: AI in Finance Specialisation by Centre for Finance, Technology, and Entrepreneurship (CFTE)

This self-paced course covers AI foundations, technologies, and enterprise implementation in finance. It includes video lectures, case studies, and projects.

Key Topics Covered: AI technologies, finance use cases, and enterprise implementation.

Target Audience and Skill Level: Accessible to all career stages; requires self-motivation.

Pros:
• Flexible learning with digital certificate.

Cons:
• Requires self-motivation for self-paced learning.

Best For: Finance professionals seeking flexible AI learning.

Course 18: AI Applications in Marketing and Finance by University of Pennsylvania

This free online course explores AI-driven applications in marketing and finance, covering fraud detection, risk management, and finance automation in a short, accessible format.

Key Topics Covered: AI applications in marketing and finance, fraud detection, and risk management.

Target Audience and Skill Level: Suitable for professionals seeking practical insights; short duration (6 hours total).

Pros:
• Free and short course.

Cons:
• Limited depth due to short duration.

Best For: Professionals seeking quick insights into AI applications.

Course 19: AI for Finance by Udemy

This 18-lecture course teaches Python, Keras, Scikit-Learn, and Pandas for financial forecasting. It is suitable for finance professionals with basic finance knowledge seeking hands-on coding experience.

Key Topics Covered: Financial forecasting, Python, Keras, and Scikit-Learn.

Target Audience and Skill Level: Finance professionals; requires some prior finance knowledge.

Pros:
• Affordable with hands-on experience.

Cons:
• Requires prior finance knowledge.

Best For: Finance professionals interested in coding for AI.

Course 20: Quant University Machine Learning and AI for Financial Professionals Course

This course covers machine learning in financial services, methodologies, and algorithm selection. It is designed for those with Python knowledge looking for practical coding focus.

Key Topics Covered: Machine learning methodologies, algorithm selection, and case studies.

Target Audience and Skill Level: Suitable for financial professionals with Python knowledge.

Pros:
• Live and on-demand options with practical focus.

Cons:
• Pricing requires inquiry.

Best For: Financial professionals seeking practical machine learning skills.

Course 21: Machine Learning for Trading Specialization by Google Cloud via Coursera

This intermediate course focuses on trading applications of machine learning, covering trading introduction, ML in trading, and reinforcement learning strategies. Requires SQL and intermediate ML knowledge.

Key Topics Covered: Trading applications, machine learning, and reinforcement learning.

Target Audience and Skill Level: Intermediate-level learners with prior knowledge.

Pros:
• Focused on trading applications.

Cons:
• Requires prior knowledge and is time-intensive.

Best For: Intermediate learners interested in machine learning for trading.

Course 22: Advanced ChatGPT for Finance by Maven

This intensive two-day course teaches advanced ChatGPT techniques for financial analysis, including Python integration and plugin use. It is designed for professionals seeking cutting-edge AI tools in finance.

Key Topics Covered: Advanced ChatGPT techniques, financial analysis, and Python integration.

Target Audience and Skill Level: Suitable for finance professionals; requires prior knowledge.

Pros:
• Intensive focus on advanced AI tools.

Cons:
• Relatively high cost for a short course.

Best For: Finance professionals interested in advanced AI analysis.

Overall Recommendations for AI Training Courses

Each of the courses reviewed in this article provides unique benefits tailored to different managerial needs and skill levels. For IT managers seeking the most comprehensive and continually updated resource, CompleteAI Training offers an extensive library at an affordable price. For those looking to focus on AI product management and strategic leadership, the IBM AI Product Manager course is a strong choice.

Managers interested in business strategy and governance may find the AI For Business course by the University of Pennsylvania particularly beneficial. For a foundational understanding of AI technologies, courses like AI For Everyone and Introduction to Artificial Intelligence by IBM provide accessible options for beginners.

Ultimately, the best course depends on the specific goals and current expertise of the learner. By considering the course content, target audience, and pros and cons outlined in this guide, IT managers can select the most suitable training to enhance their AI capabilities and leadership effectiveness.