Web Age Case Studies

Case Study
AI Data Science Upskilling Program
Client: A major international consulting firm


Be able to compete for high-level projects, secure lucrative contracts, and gain a significant edge over competitors. Recognizing the transformative power of AI in their industry, our client wanted to proactively invest in upskilling their workforce with cutting-edge data science and AI expertise.


Through in-depth interviews and targeted pre-assessments, we identified our client's skill gaps, AI use cases across their organization, and implementation goals. Understanding their transformation vision and existing policies and procedures allowed us to tailor the program effectively.

Furthermore, we fully integrated their concerns regarding ethical AI, security, and explainability. For example, we addressed their desire to understand the core ethical principles of AI, including fairness, transparency, and global regulations. Additionally, we understood their need to incorporate building secure AI models and detecting potential bias sources. This proactive approach ensured alignment with their vision for responsible and trustworthy AI implementation.

To ensure the participants could confidently tackle advanced topics like Natural Language Processing (NLP), coding logic, and debugging, we started the program by establishing a strong foundation in calculus, statistics, and algebra. These core mathematical skills are the building blocks for data science and AI. We also incorporated:

  • A blended learning approach, combining instructor-led online sessions with interactive exercises and access to a dedicated learning platform with resources and self-paced activities.
  • Having the program culminate in a hands-on project that integrates all acquired knowledge, allowing attendees to apply their new data science and AI expertise to solve a real-world problem.


Web Age Solutions designed a comprehensive AI Data Science Upskilling program tailored to the specific needs of our client and its employees. The program covered key topics, including:

Machine Learning:

An exploration of the entire Machine Learning (ML) process,from supervised and unsupervised learning techniques to feature engineering and building a robust data processing pipeline. Additionally, the program focused on Natural Language Processing (NLP) applications of ML.

Deep Learning:

Deep dive into the building blocks of Deep Learning (DL),including Feedforward Neural Networks, Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs). The program further explored the application of DL for text and NLP tasks.

Generative AI:

Demystifying different types of generative models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs),and Large Language Models (LLMs). Participants gained hands-on experience with Generative AI tools and APIs, learned about fine-tuning and customization, and explored explainability and responsible use practices.

AI Security:

Addressing the critical aspect of AI security,the program covered the AI security landscape, including threats,vulnerabilities,and attack vectors. Participants gained an understanding of AI vulnerabilities and learned to secure the entire AI lifecycle.


Case Study
Data Science and Machine Learning Upskilling Program
Client: A major international consulting firm


To fast-track new hires to tackle high-impact projects, our client sought a comprehensive Data Science (DS) and Machine Learning (ML) upskilling program. Recognizing the industry's shift towards DS and ML, they wanted to equip their workforce with cutting-edge expertise in MLOps, DataOps, AWS, Spark, and GitLab integration for their projects.


Through in-depth interviews and targeted pre-assessments, we identified our client's skill gaps, ML use cases across their organization, and implementation goals. Understanding their transformation vision and existing policies and procedures allowed us to tailor the program effectively.

Strategic Skill Matching

We recognized the client's critical need to align their training program with client requirements. This ensures new hires are matched with suitable clients, maximizing their ROI by equipping them with the specific skills each client requires.

Curated On-Demand Learning Library

To optimize the client's existing on-demand course library, we thoroughly reviewed their Udemy library and selected courses that aligned with the program's specific requirements. This saved the client significant time and resources by eliminating the need for independent course research.

This allowed us to incorporate a blended learning approach, combining instructor-led online sessions with interactive exercises and access to a dedicated learning platform with resources and self-paced activities.

The program culminated in a hands-on project that integrates all acquired knowledge, allowing attendees to apply their new data science and ML expertise to solve a real-world problem. By forming collaborative groups, participants gained a deeper understanding of the technology while developing essential teamwork skills. This mirrored real-world scenarios, ensuring a smooth transition into their roles.


Using a combination of courses created by Web Age Solutions, custom developed projects, and official AWS curriculum, we designed a comprehensive machine learning upskilling program tailored to the specific data science needs of our client and its employees. The program covered key topics, including:

  • Data Analytics on AWS: AWS' Data Analytics services and capabilities includes S3, QuickSight, AWS Glue, and more. Students learn the data-related aspects of these services, enabling them to select services to match their use cases effectively.
  • AWS Cloud Practitioner Essentials: Attendees gain a solid understanding of the Amazon Web Services (AWS) Cloud, independent of specific technical roles. This course also helps prepare learners for the AWS Certified Cloud Practitioner exam.
  • CI/CD with GitLab: Git has become the most popular version control system for automating and managing infrastructure. Learners were immersed in the world of DevOps, including version control with Git, GitFlow, and Continuous Integration with GitLab.
  • Spark and ML at Scale: Spark and its related technologies allows developers to build, deploy, and maintain powerful data-driven solutions. Attendees learned how to use Spark's ML libraries, focusing on data preprocessing, feature engineering, model training, and evaluation.
  • DataOps: Implementing Data Operations (DataOps) practices correctly improves the speed and accuracy of data insights compared to traditional methods. Learners mastered Data Engineering, DevOps, Agile, and Lean Manufacturing principles to improve data analytics and reduce repetitive tasks and manual processes.
  • Applied Data Science and Practical ML with AWS SageMaker and AutoML: Developing and deploying cutting-edge machine learning models solves real-world business challenges. In this course, learners gained a comprehensive understanding of ML and worked with the latest tools and techniques to build intelligent, impactful applications.
  • MLOps Engineering on AWS: Machine Learning Operations (MLOps) extends the DevOps practice. This official AWS course taught attendees how to successfully leverage data, models, and code for successful Machine Learning (ML) deployments using Amazon SageMaker.


Case Study
Amazon Web Services (AWS) Upskilling Program
Client: Fortune 500 Financial Services


A Fortune 500 financial services leader in the Midwest faced a critical challenge: building an AWS-savvy workforce to keep pace with their cloud objectives. Existing training programs, focused solely on earning certifications, fell short of teaching their teams the practical skills needed to master the AWS ecosystem and ensure successful cloud implementations.


To ensure a successful learning experience, we created a comprehensive plan to reinforce practical cloud skills that included:

  • In-depth, Hands-on Learning
  • Business-Driven Focus
  • Actionable Insights & Reporting
  • Knowledge Gain Metrics to validate ROI
  • Real-World Applications
  • Capstone Projects
  • Customized Learning Paths


Web Age Solutions designed a customized upskilling AWS upskilling program tailored for both new hires and existing employees.

  • The program addressed the client's specific technology stack, ensuring a seamless transition for new hires and building upon existing knowledge for current staff.
  • Recognizing the client's Agile workflow, we integrated Agile best practices throughout the learning program delivering the content in manageable sprints for optimal knowledge retention.

Beyond rote memorization, Web Age understood the importance of long-term skill retention and practical application.

  • Our program incorporated 50% hands-on labs and workshops, fostering a deep understanding of the AWS ecosystem.
  • To further solidify learning, we collaborated with the client's subject matter experts (SMEs) to develop a capstone project directly tied to their business goals.
    • This project, delivered in three sprints, provided participants with a real-world challenge to apply their newly acquired skills and demonstrate the interconnected nature of AWS technologies.


Web Age Solutions' commitment to delivering impactful training has resulted in a long-term partnership with this valued client. The program's success has led to multiple deployments over the past two years, solidifying our position as a trusted advisor in our client’s AWS journey.


Case Study
Software Engineering for Career Mobility Upskilling Program
Client: A Fortune 100 Insurance Company


A large insurance company discovered a troubling trend: high turnover among Associate Software Engineers (SWE1). This coincided with many open Software Engineer 2 (SWE 2) positions.

Further investigation revealed:

  • The firm expected Software Engineers (SWE 1) to be promoted to SWE 2 (“practitioners”) after 3-5 years.
  • However, the average tenure in the SWE 1 role was 5-8 years.

This created a double challenge:

  1. A lack of qualified internal candidates for SWE 2 roles. The lack of eligible internal candidates forced our client to rely on external hiring, driving up recruitment costs.
  2. SWE 1 employees, stuck in their positions for longer than expected, sought promotions elsewhere due to limited advancement opportunities within the company.


  • Due to the critical roles within their teams, extensive training programs were impractical for SWE 1s.
  • A one-size-fits-all approach wouldn't address these engineers' need to develop specialized skill sets.


Web Age Solutions built a customized accelerator program to bridge the skills gap between SWE1s and SWEs 2. The program met the client’s requirements to:

  • Target specific job roles where a disruption to the career pipeline has been identified.
  • Promote advancement within the organization and remove any obstacles.
  • Remove bottlenecks for career progression.

Web Age Solutions created a series of skills accelerators. These short programs (varying from 5-15 days in duration) would:

  • Target specific technology tracks for focused learning.
  • Bridge the skill gap with the necessary knowledge for advancement.
  • Be delivered in manageable time blocks for minimal disruption.
  • Leverage the client's preferred learning libraries for self-paced reinforcement between instructor-led sessions.
  • Foster a collaborative learning environment through group participation.
  • Provide an interactive and immersive learning experience.

Upward Mobility

This process created a pipeline for career advancement:

  • Upskilled employees gain the qualifications for internal promotions to SWE 2 positions.
  • The open positions at the SWE 1 level are filled by qualified junior staff, promoting overall career growth within the organization.

The SWE1 journey consists of 4 Accelerators. SWEs will attend the accelerator(s) most relevant to their career progression. SWEs may attend mulitple accelerators, or only one, as appropriate.

  • Projects were tailored to reflect the work participants will be expected to do on the job.
  • Cloud was maintained at per student level.
  • A discussion group was created and maintained for each cohort through out each accelerator, monitored by the instructor.


Case Study
Large-Scale Product Thinking Training
Client: A Fortune 100 Insurance Company


A project-driven (rather than product-thinking) mindset at our Fortune 100 insurance client led to:

  • Reduced customer satisfaction due to slow product updates.
  • Delays in new product launches hinder market competitiveness.
  • Difficulty adapting products to meet evolving market demands.

Recognizing the limitations of a project-driven agile approach, the organization wanted to cultivate a culture of product agility to ensure a higher ROI.


This new mindset would be anchored in Design Thinking and Lean Startup best practices, both methodologies renowned for focusing on customer engagement.

While large-scale projects will remain a reality, fostering a "Product Agility" mindset among product owners is crucial. This approach prioritizes continuous iteration and improvement, meaning that:

  • Instead of a one-shot delivery model, developers test ideas before full implementation.
  • Functionality is no longer a "deliver and forget" proposition; ongoing customer feedback must become integral to the process.
  • The continuous learning loop fuels the development of new ideas and product enhancements.


The training catered to both individual and team needs. Open enrollment courses were available for general participation, while dedicated team workshops offered customized training. Before each dedicated session, a curriculum call was held to discuss the team's specific goals, challenges, and audience. This ensured that the tailored content aligned with the organization's overall messaging and approach, while remaining impactful for each unique team.

Web Age Solutions worked with our client to set enterprise-wide training priorities regarding building a product mindset program. These included:

  • Understanding Project-Driven initiatives vs. Value-driven
  • Defining Product Strategic Goals
  • Creating Value-Driven Initiatives & EPICS
  • Defining the role of Product Managers and Product Owners
  • Demonstrating the key facilitation skills necessary to transition from a tactical focus to a more strategically focused approach
  • Applying Design Thinking and Lean Startup, including creative strategies for planning a portfolio or product backlog using the Mobius Loop
  • Refining learnings from class by applying concepts directly to a problem\enhancement that the company is currently facing.
  • Understanding the role of Problem-finding and Problem-Solving. (Create, refine, and test real solutions on real customers and stakeholders.)
  • Creating responsive Product Roadmaps


The client has significantly shifted their team's understanding of how products can directly address customer needs.

This newfound "Product Agility" mindset has yielded benefits: higher customer satisfaction, improved adaptability to market changes (faster pivoting), and reduced rework, leading to an increased ROI.


The first workshop was delivered in February 2022.

The pilot was so successful that other teams within the organization soon requested this training. The client continues to partner with Web Age Solutions for ongoing workshops, ensuring the product mindset permeates the entire organization.

Courses taught in the program included offering from our Product Thinking Training line: