Discover Affordable Day 1 CPT Programs Near Boston at New England College (NEC)

Through this course, students will learn to use SQL to collect and analyze data from relational database sources. The course will concentrate on the proper construction of the SQL queries that are the basic access tool used in data dictionaries, data modeling, and data mining processes and procedures. At the completion of this course, students will have the ability to build, query and manipulate database structures and to format information critical to the process of informed business decision making. Credits: 3 Students cannot take both CT 5610 Database Design and CT 5130 Introduction to SQL for Data Analytics for credit.

This course is about foundational tools used in data science with the primary focus on R programming language. R is a necessary tool to be successful in the field of data science. The course will teach basic data structures in R and fundamental libraries needed to analyze data. The course will specifically cover in a case study based applied setting, reading various forms of data into R, cleaning, merging, and organizing of data, loops and functions, basic statistical functions, visualization, and exploratory data analysis.

This course introduces students to the principles and practice of analytics through statistical modeling and data management. Many business problems still utilize traditional statistical and data mining tools. This course introduces several modeling tools like multiple linear and logistic regression (MLR), Hierarchical linear model (HLM), multiple discrimination analysis, factor analysis, introduction to Bayesian statistics, and cost and objective functions. In addition, it introduces Monte-Carlo simulations and rules of probability distributions.

This course helps develop an understanding of the relationship between the human visual perceptual system and the design and evaluation of information visualizations that inform, educate, and promote analysis. Students will learn to build interactive dashboards and tell compelling stories with charts and graphs based on geospatial, univariate, multivariate, relational, text, and other forms of data. They will also learn to see their design ideas from other perspectives to help evaluate the effectiveness of particular elements of visualizations and think critically about each design decision. Credits: 3 Student cannot take both CT 6445 Visual Analytics and CT 6440 Information Visualization for credit.

This course provides an introduction to computer programming in Python, a popular, easy-to-learn, cross-platform language with extensive libraries. Students will learn to recognize problems appropriate for computer program solutions, to determine the requirements of those solutions, and to translate those requirements into procedural programming constructs using object-oriented programming methodology. Students will then use basic Python commands to access databases, analyze data, and develop data-driven decisions.

The Web Analytics class reviews the tool and techniques associated with the collection and measurement of web data that is used for purposes of web optimization and the analysis of web traffic. A primary goal of the course is to train students in the methods used to gather and report on that data and its use in business and market research. Students will also be introduced to the concept of web scraping, a process that involves the automated extraction of data from target web sites for the purposes of further reporting and analysis.

Students will use powerful tools and methods in spreadsheets to analyze data, design charts and graphs, create forecasts and models, and communicate the insights derived from those insights. In this course, students will learn how to generate table summaries, outline and group data, use complex formulas and IF statements, work with functions, create pivot tables, format pivot charts, perform what-if analysis with Goal Seek and Solver, and explore the various lookup functions. The class will also explore the uses of the Data Analysis Tool Pak for Random Number Generation, Annova, correlation, covariance, F & T tests and more.

Information is stored in both structured and unstructured forms. One of the prominent unstructured forms of data collection is text. Numerous advances have been made in capturing the essence of such data through algorithms and techniques that fall under the umbrella of natural language processing. This course will cover the fundamentals of language model with the focus on analyzing textual data through transformation to machine-readable data, various types of weighting for documents and tokens, sentiment analysis, semantic analysis, and clustering.

This course covers various non-linear algorithms necessary to perform both supervised and unsupervised learning analysis for modern business analytics problems. The emphasis is on application of ML through case studies from industries such as aviation, sports, healthcare and banking. Various topics covering prediction problems related to classification and regression, partitioning techniques, clustering and dimension reduction will be discussed. Python will be used throughout the course.

Today, business can collect and store huge volumes of data. New tools enable big data scientists and engineers to analyze that data to gain insight and to extract meaningful trends and patterns. This course will introduce the student to the collection, storage, processing, analysis, and visualization of big data using Hadoop with MapReduce and Spark. Learners will begin to understand the procedures used for resolving real world business challenges involving big data.

This internship series allows students to overlay the academic and theoretical study of Data Analytics with practical experience in the field. Students have the means to apply academic concepts to solve real world business problems.  The internship is designed for students to better understand the work expectations and individual organizational culture.

This course is an introduction to the wide range of topics that encompasses computer security. It is designed to provide a foundation for an advanced study of issues related to digital devices, networks, data systems, cryptography, and information management. Upon completion of this executive program in cyber security, both the IT and the general business professional will be equipped to manage the wide variety of security challenges and threats faced by businesses and industries across the globe. 

This course covers database vulnerabilities and defenses. Students will become familiar with methods for preventing unauthorized access, leakage, or loss of data.  It introduces technologies for database protection, access control, and auditing as well as best practices for database hardening. Students will explore the benefits and drawbacks of centralized and decentralized data storage through exposure to Hadoop. They will analyze government policy and regulatory compliance through an introduction to HIPAA and other regulations affecting the storage of sensitive or restricted data.

This course integrates law, ethics and cybersecurity. The course examines laws related to privacy, intellectual property, civil litigation, criminal prosecutions, and, of course, cybersecurity. Students will identify and analyze the policies reflected in those laws. Students will explore several applicable ethical frameworks and apply them to various scenarios. Students will examine their responsibilities related to the handling of data as it pertains to legal, ethical and/or agency auditing issues, and how the type of legal dispute (civil, criminal, private) affects the evidence used to resolve an issue.

The ability to secure information within a modern enterprise is a growing challenge. Threats to information security are global, persistent, and increasingly sophisticated. Effective information security requires participation, planning, and practice. This course is designed to teach students the basics of information security, in both the management aspect and technical aspect. The course addresses a range of topics, each of which is vital to securing the modern enterprise. These topics include plans and policies, enterprise roles, security metrics, risk management, standards and regulations, physical security, and business continuity. The course will emphasize the practical implications of cybersecurity management through the application and study of timely examples.

This course aims to provide configuration guidelines for network infrastructure security. It first reviews the key components of a network infrastructure, and then points out the differences between information security and infrastructure security. Network Infrastructure includes network devices such as routers, firewalls, switches, servers, workstations, and other devices, as well as, the software running on these devices. This course will highlight the technologies and security methods that make sure that every time a configuration is changed or new device is added, a security hole is not created in the network.

Cloud computing introduces new privacy and security risks that are not present in traditional data centers. This course is about these concerns and the appropriate policies and responses for a cloud environment. The course begins with an overview of cloud computing and virtualization which provides the necessary background for understanding these issues. Additional topics include access control, identity management, denial of service, account and service hijacking, secure APIs, malware, forensics, regulatory compliance, trustworthy computing, and secure computing in the cloud.

This course is designed to teach students to help identify potential threats on a computer or network. An ethical hacker attempts to systematically penetrate a computer system by bypassing system security and by searching for weak points that could be exploited by malicious hackers. This information may then be used by an organization to improve overall system security. Working with both hardware and software developers, ethical hackers work to uncover the security vulnerabilities that a malicious hacker could potentially exploit.

This course provides information system users with the knowledge of their roles and responsibilities towards protecting information system assets. Topics will include workstation and office security, types of malicious programs such as viruses, access control mechanisms, IT governance and security management. This course will also lay a foundation for students to pursue further studies of systems security and protection issues such as terminology, threats to information resources, computer abuse, and system vulnerabilities. This course will map to many topics included in the CompTIA Security+ Certification.

This course will introduce the principles of collection, preservation, examination, and analysis of computer evidence. Students will learn the evolving law of acquiring and analyzing digital evidence from computers and devices. Additional topics will include: computer crime, intellectual property, privacy, risks, vulnerabilities, countermeasures, and the presentation of legal evidence in a court of law.  National and International standards for privacy and data rights will be discussed along with personal data security at border crossings. This course will cover a brief history of gray hat hacking and will include both theoretical and practical labs.

The Practicum/Internship allows students to overlay the academic and theoretical study of Computer Information Systems with practical experience in the field. Students have the means to apply academic concepts to solve real world business problems.  The Internship is designed for students to better understand the work expectations and individual organizational culture.

This course will examine and apply numerous practices and procedures utilized to manage complex projects from start to finish.  The course will examine the various tools including GANTT and PERT charting, scheduling, budgeting, costs, and resource allocation. The course will identify the role of teams and human resources including staffing, negotiations, and conflict resolution and the relationship to developing and implementing successful projects throughout the organization.

This course will explore and apply managerial decision-making in support of the continuous improvement required to create a total quality work environment. Students will research and execute decisions around leadership capabilities, statistical quality controls, and processes designed to improve root cause analysis and implementation of quality driven strategies. Persistent change techniques including Lean, and Six Sigma will be examined, and an outline of national quality honors (Baldrige) and global quality conformations (ISO) is introduced.

Managers routinely make decisions with imperfect knowledge and where a degree of risk exists. Through cases and projects students will confront making decisions involving risk. While primarily designed to provide students with the quantitative tools necessary to make and articulate these decisions, understanding qualitative frameworks in which decisions are made will also be examined.

IT project managers have the responsibility of the planning, procurement and execution of a project through various resources and stakeholders. Topics include the leadership responsibilities of creating effective teams, organizations and cultures; the exploration of different leadership styles; and applying change management to current projects and teams.

Today's companies need project managers with good communication skills to foster teamwide trust and eliminate conflict and confusion.  

Project managers must envision a project and make this vision understood by those around them. Students will develop the ability to select and apply best practices in researching information, writing project related documents, and creating effective presentations for stakeholder buy-in.

Effective project managers need to be able to utilize a variety of tools in the formation, development, and potential interpersonal conflicts among teams. Students will develop an understanding and the ability to apply change management. Topics include but are not limited to configuration and formal change control process and business process reengineering.

Applying economic criteria to alternate designs and proposals, students will explore various methods to measure productivity and value. Students will examine and analyze aspects of planning, managing, and controlling IT purchasing and finance. Internal and external factors including the management of contractors and subcontractors in support of best practices and the efficient management of available resources will also be explored.

The moral implications of leadership and decision making when managing projects are explored with respect to their social impacts, and the challenge that exists between achieving desirable project outcomes. This course explores and analyzes the interrelationships and key ethical issues that can arise from each. Topics include but are not limited to collective decision making, liability, privacy issues, and social responsibility.

Information security concerns should always be a priority when managing project risks. This course will help students ask the right questions, measure risk maturity levels, determine ways to handle sensitive data, and ways to implement IT security risk strategies.

Project managers need to identify risks, errors, or defects and implement strategies and tools necessary for process improvement. Through Lean management techniques, students will implement tools and decision-making to maximize value and minimize waste while optimizing project and their overall portfolio.

In this capstone course, students will use various skills introduced in the previous series of IT Project Management courses to define, plan, execute, control, and close a simulated project. This will include developing key deliverables from facilitating meetings to justifying decisions for the benefit of key stakeholders. Students will also use software tools or templates to develop the necessary artifacts that are commonly used in any large-scale project.

This internship allows students to connect and apply the academic and theoretical study of project management with practical experience in the field. Students have the means to apply academic concepts to solve real world business problems. The internship is designed for students to better understand the work expectations and individual organizational culture while developing and managing projects.