AI Fundamentals & Automation

Admission Requirements

To enroll, applicants must provide:

• Government-issued identification.
• Passport-style photo or selfie.
• Evidence of English language proficiency.
• Official transcript verifying a bachelor’s degree from:
  • An accredited U.S. institution or international equivalent.
• Translations for non-English documents provided by:
  • A validated institutional official or embassy.
• Self-certification of high school completion or equivalent (e.g., GED or national exam certificate).

Note: Nexford’s Office of Admissions may request additional verification of self-certified documents.

Required Courses

AIA2100 Introduction to AI

Introduction to AI highlights the goal of artificial intelligence, which is to create software that can perform reasoning tasks and solve problems in complex environments the way humans do. This course begins with an overview of the evolution of AI tracing its history from the work of Alan Turing to the current state of the art software. Learners examine a range of AI techniques and their applications in business contexts, including knowledge representation, both basic and heuristic search, probabilistic modeling with Bayesian networks, and natural language processing techniques. Class discussions and readings address the philosophical and ethical implications of developing and deploying AI systems in a range of contexts. In the culminating course project, learners identify a problem or task that AI could effectively address, select and evaluate specific AI techniques, and identify and evaluate potential ethical questions surrounding the solution.

BAN3200 Machine Learning and Predictive Analytics

Machine Learning and Predictive Analytics helps learners understand how in today’s global business markets organizations have the opportunity to reach a wider consumer base for their products, and as this consumer base expands, the need for a more sophisticated approach to data mining, analysis, and application is increasingly evident.

This Predictive Analytics course focuses on the use of predictive analytics and the use of machine learning to find patterns in data sets; the organizations that can better understand the data they collect along with being able to make predictive calculations from that data will gain competitive advantages in their respective markets. In this course learners examine the tools and techniques of predictive analytics and machine learning, including regression analysis, decision trees, and rule models. Learn predictive analytics, and gain a better understanding of how to predict outcomes from available data. Learners explore and examine data, apply predictive tools and techniques to predict outcomes from the data, and interpret the results for improved decision making during this predictive modelling course.

AIA3200 Foundations of Robotics and IoT

Foundations of Robotics and IoT engages learners in understanding how the interconnectivity of devices via the Internet is harnessed to improve robotic manufacturing processes. This course provides an overview of IoT architecture. Within the context of IoT ecosystems, learners explore software product design with cyber models, application modeling, IoT value modeling, and hardware product design with sensors, embedded systems, and connected sensors. Topics also include an overview of the network fabric in IoT, operational technology (OT), information technology (IT) and fog networks, IoT product cloud, and IoT platforms. This course provides an overview of intelligent process automation (IPA) and five major technologies supporting robotic process automation (RPA): smart workflow, machine learning, advanced analytics, natural-Language generation, and cognitive agents.

AIA3250 Fundamentals of Cybersecurity

Information is the lifeblood for organizations of all types. Therefore everyone needs to have a fundamental understanding of the interdisciplinary field of cybersecurity. This course provides this fundamental knowledge by taking the learner through the evolution of the discipline from information security to cybersecurity. Learners evaluate several important laws, which have significant impact on cybersecurity strategy.

Learners also investigate multiple cybersecurity technologies, processes, and procedures; they learn how to analyze threats, vulnerabilities, and risks in these environments, and develop appropriate mitigation strategies by applying a mission-focused and risk-optimized approach.

This survey course introduces learners to the three primary sources of threats (technology, policy, and people, both internal and external) and the three classes of tools: technology, policy, and people used to develop an organizational cybersecurity strategy. This course and exercises are designed to emphasize, encourage and enhance the critical thinking abilities of learners. Although the course is not designed to prepare learners for this test, the material covered in this course includes most of the knowledge tested in the CompTIA Security+ exam.

Learners will apply their learning by performing systematic case studies of actual organizations.

What You'll Learn

• Discover how AI technology like automation and cybersecurity transforms businesses and contribute to economic growth
• Gain soft skills of the future like critical and creative thinking
• Learn hard skills like applying automation technology in your business and career to create intelligent workflows
• Keep up with the fast-moving field of AI and lead with confidence: 94% of Nexford learners increased in confidence at work
• Build a network of global professionals from 110+ countries working at firms like Google, TikTok, Deloitte, and EY
• Earn a certificate as well as digital badges as you go – including credentials from LinkedIn Learning

Graduates of this certificate program will be well-prepared to pursue roles such as:

• AI Specialist
• Data Analyst
• Cybersecurity Analyst
• IoT Specialist
• Automation Consultant