CFO

Data Science, Data Analytics and Coding Courses for Finance Executives

By Megan O’Brien, finance & business editor
December 9, 2021
data science courses

In short:

  • The CFO role and the nature of the finance department as a whole are evolving, leaving many lacking the skills to propel their organizations forward.
  • In order to move their departments toward automation, finance leaders should work to understand the language of data experts and the processes of coders, according to author and CFO Glenn Hopper.
  • We outline our choice of continuing education courses for finance executives looking to advance their data science, data analytics and coding skills.

Plenty of articles declare that the CFO’s role is changing and requires new skills. CFOs need to become more strategic, more data-driven and more tech-savvy, these stories say. What the business press fails to mention is how finance leaders are to pull this off.

You know the thesis: Finance departments should no longer be transactional, simply providing historical data on command. Rather, effective finance teams are analytical, working with real-time data and heading the charge toward finance and operations automation.

In his recently-published book “Deep Finance: Corporate Finance in the Information Age,” longtime CFO Glenn Hopper outlines steps his fellow finance leaders can take to fill their new roles as “part finance guru and part data scientist.” In addition to outlining the fundamental concepts and technologies involved in the “age of analytics,” Hopper recommends CFOs take courses in the relevant subjects.

“In order to seize [the opportunities presented by finance automation], you and your team must make a plan … to shed the burden of manual processes and spend your time on higher-level tasks,” writes Hopper. “This requires thinking like a coder and speaking the language of developers and data experts. If you can’t speak intelligently, distinctly and thoroughly about the plan, then you’re not likely to get the buy-in you need.”

It’s important to note that Hopper is the CFO of an eDiscovery service provider. His company takes very large unstructured datasets from clients and mines them for data and correspondence relevant to lawsuits. For him, understanding the business of his company means that he needs to be fluent in topics like machine learning and big data analysis. That’s not the case for most finance executives. Even so, an understanding of foundational concepts and technologies in programming and data will prove valuable as CFOs look to create a data-driven, automated organization.

Here are our suggested courses for finance executives in the areas of data science, data analytics, business intelligence and programming.

How we compiled this list

We looked for courses that satisfied several criteria:

  • They needed to be online, allowing users to take them anywhere.

  • Unless otherwise noted, all courses are self-paced, a key for time-strapped executives.

  • We looked for highly-rated programs that cover a wide range of topics at a high level.

  • All programs are formulated for continuing education and have no prerequisites. We selected courses from several providers with a range of prices.

We assigned each course a level based on the required time commitment and depth of study since finance executives require varying amounts of knowledge based on their industry, point in career, company support, time available and personal inclination.

  • Level 1: Programs with fewer than 10 hours of coursework. Cover the fundamental concepts of the subject at a high level. Best suited for those seeking a simple overview of a topic.

  • Level 2: Programs with 10-35 hours of coursework. Provide a more in-depth look at the subject and cover the practical components of using big data and its associated technologies. Best suited for those looking toward implementation.

  • Level 3: A professional certification in the subject requiring more than 80 hours of coursework. Dives deep into the concepts, equations, techniques and technologies involved. Best suited for professionals in data-focused business who want to become experts in the topic.

Coding Courses

Level 1: Learn How to Code

Provider: Codecademy

Duration: 6 hours

Format: Online, self-paced

Price: $19.99 per month for a Codecademy Pro membership

Steve Jobs once said, “Everyone should learn how to code; it teaches you how to think.” Learning to code can teach CFOs how developers think, a useful skill when trying to understand a technology’s potential benefit for finance. This language-agnostic course covers fundamental programming concepts like variables, functions and control flow. Codecademy also provides a curriculum for business-related technical training.

Level 2: Programming Fundamentals

Provider: 18 hours

Duration: Duke University through Coursera

Format: Online, self-paced

Price: $49 per month

This course is the first in a series: Introduction to Programming in C offers lessons that extend to any language you might want to learn. Taught by Duke University faculty through Coursera, the curriculum covers problem solving with programming, as well as how to develop an algorithm, read code and how programming concepts relate to algorithms.

Level 3: Certificate Program in Software Development and Programming

Provider: University of California at Berkeley

Duration: 150 hours

Format: Online, self-paced

Price: $4,000 (on average)

The University of California at Berkeley, one of the top-ranked computer science schools in the country, offers an online professional certificate in software development and programming for those who want to write code as part of their job. The curriculum consists of five to six required courses (depending on specific courses taken) for a total of 10 semester units, with no formal prerequisites required.

Data Analytics Courses

Level 1: Introduction to Business Analytics 2021

Provider: Udemy

Duration: 5 hours of on-demand video

Format: Online, self-paced

Price: $99.99 for the course or $29.99 per month for a Udemy subscription

Udemy’s introductory course on business analytics is formulated for those who want to apply analytics to monitor their organization’s performance. The curriculum covers end-to-end process mapping, internal and external benchmarking and various types of analysis, including historical, variance, trend and value-based. Executives and ambitious managers can take this course to build a strategic plan for leveraging data to improve performance at their business.

Level 2: Applied Business Analytics

Provider: MIT Sloan School of Management

Duration: 6 weeks, 4-6 hours per week

Format: Online, instructor-led

Price: $2,800

In this six-week program conducted by MIT Sloan School of Management, senior executives, functional managers and business heads come together to learn how to turn data into a competitive advantage. Participants will learn best practices for data analytics process management, including establishing workflows, identifying interdependencies and recognizing when to utilize human judgment. MIT also provides weekly office hours with learning facilitators and discussion boards on industry-specific topics. This course is instructor-led with cohorts of 300-400 students starting quarterly.

Level 3: Business Analytics: From Data to Insights

Provider: The Wharton School of the University of Pennsylvania

Duration: 3 months, 6-8 hours per week

Format: Online, self-paced

Price: $2,600

This certificate program provides an understanding of how analytics can improve your decision-making process. Formulated for managers and executives, it covers the three core pillars of analytics: descriptive analytics, predictive analytics and prescriptive analytics. The course helps students look at data and identify insights, make predictions for the long term and prescribe data-driven actions to their organizations.

Data Science Courses

Level 1: Data Science Foundations

Provider: LinkedIn Learning

Duration: 4 hours

Format: Online, self-paced

Price: $29.99 per month for a LinkedIn Learning subscription

Accountants, listen up: LinkedIn Learning is registered with the National Associate of State Boards of Accountancy (NASBA), meaning this course counts for 9.6 CPE credits. Hit two birds with one stone while upping your technology chops. This introductory course covers the various sources of data, components of effective data visualization and the role of mathematics, applied statistics and machine learning in data science.

Level 2: Intro to Data Science

Provider: Udacity

Duration: 2 months

Format: Online, self-paced

Price: Free

They say the best things in life are free, and indeed, this thorough data science introduction from Udacity comes at no cost. A good fit for those who want an overview, the curriculum covers a wide range of foundational data science concepts. Topics include data manipulation, data analysis with statistics and machine learning, analysis through data visualization and working with big data.

Level 3: Data Science for Executives

Provider: Columbia University through edX

Duration: 4 months, 7-10 hours per week

Format: Online, self-paced

Price: $267.30

In this professional certificate program, participants learn the fundamental techniques of data scientists and their real-world applications in decision-making. The program is geared toward executives who want to learn more about statistical analysis, machine learning and how data will impact businesses in the future. It’s broken into three sections, each of which takes about five weeks to complete: statistics for data and analytics; machine learning for data science and analytics; and enabling technologies for data science and analytics.

Artificial Intelligence (AI) and Machine Learning (ML) Courses

Level 1: Artificial Intelligence for Finance, Accounting & Auditing

Provider: Udemy

Duration: 5.5 hours of on-demand video

Format: Online, self-paced

Price: $84.99 for the course or $29.99 per month for a Udemy subscription

The term “artificial intelligence” is frequently thrown around without context about its practical business application. This course from Udemy remedies that with a deep dive into AI as it relates to finance, accounting and auditing. The eight AI areas of application covered include: chatbots, natural language processing, machine learning, machine vision, speech recognition, internet of things, robotic process automation and smart analytics. The program is formulated for professionals with all levels of knowledge in business, finance, accounting and auditing — no technology background or coding required.

Level 2: Artificial Intelligence for Business

Provider: The Wharton School of the University of Pennsylvania

Duration: 4-6 weeks, 2 hours per week

Format: Online, self-paced

Price: $599

This course covers the fundamentals of big data, AI and ML — and, more importantly, how to use them to support your organization’s business strategies. The curriculum is designed to provide learners with insights into established and emerging developments in AI, big data and ML in finance, as well as the operational changes AI will bring. In addition to real-life examples, the course walks through the practical points of implementation and governance.

Level 3: AI Applications for Growth

Provider: Kellogg School of Management at Northwestern University

Duration: 2 months, 4-6 hours per week

Format: Online, instructor-led

Price: $2600

A professional certificate within the Kellogg School’s executive education offering, Northwestern University's AI Applications for Growth is geared towards experienced executives, managers and consultants looking to implement AI. It is also ideal for investors seeking a deeper understanding of the area. The 2-month curriculum provides frameworks to build an effective AI implementation plan for your organization. This program is instructor-led with cohorts of 300-400 students starting quarterly.

The bottom line

As Hopper writes, you don’t have to be able to build an app to revolutionize your finance operation. Leaders who have a strong grasp of the core concepts behind data, business intelligence and programming will be indispensable to organizations moving forward.

  

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