[Discuss Your Training Program]

MWH designs and delivers AI training programs that change what people can actually do — not what they can recite. From enterprise bootcamps embedded in Fortune 500 L&D to university AI curricula deployed across disciplines, we build capability that outlasts the engagement.

Most AI training programs are structured for compliance: attend the workshop, earn the certificate, return to business as usual. MWH builds programs structured for transformation. Our curriculum frameworks are designed by practitioners who have implemented AI and ML systems at enterprise scale — at companies including Google, Square, Paramount, and Uber — and then adapted for the specific learning needs of each audience. Whether we are designing an AI curriculum for a Southern University program, running a corporate digital transformation academy for Chevron and Texaco, or building government capacity in emerging markets, the standard is the same: learners leave able to do things they could not do before.

Discuss Your Training Program

What We Do

MWH Group's Learning & Development practice covers the full spectrum of AI workforce development: corporate training programs embedded in enterprise L&D, university-level AI curriculum design through our AtkCo joint venture, government capacity-building programs in Africa and beyond, and executive AI education for leadership teams navigating digital transformation. We design for specific audiences, not generic skill levels. A STEM student entering an AI/ML specialization needs a different program than a marketing director who needs to understand what AI means for her team's workflow — and we build both.

Our delivery formats match real organizational constraints. Self-paced online modules for distributed corporate teams who cannot align schedules. Instructor-led cohorts for organizations that need accountability and peer learning built into the model. CoE-in-a-Box for enterprises building an internal Center of Excellence that needs curriculum, governance, and operating playbooks packaged together. Every format is designed with a defined capability outcome, not just a training hours target.

The AtkCo joint venture extends our academic reach, bringing MWH's practitioner knowledge into formal university contexts with accredited curriculum frameworks and established relationships with academic institutions. Our internship program gives students real-world project experience within MWH mandates — not simulated case studies, but live work on actual client problems. This is how we close the gap between what universities teach and what enterprises need.

Our Approach

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Step 1 — Audience & Capability Gap Assessment

We begin by mapping the specific audience: their current AI literacy, their role-specific use cases, the organizational context they'll apply training in, and the gaps that most limit performance. Corporate L&D, university students, government staff, and executives each have distinct starting points and distinct destinations. We design from the destination backward.

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Step 2 — Curriculum Architecture

We build modular curricula with explicit learning outcomes at each stage. STEM-track programs include hands-on ML model building, data pipeline work, and agentic AI frameworks. Non-STEM programs focus on AI for specific disciplines — marketing analytics, operations decision-making, legal document review, financial modeling. Faculty programs include pedagogical frameworks for AI-augmented teaching. Each module maps to a measurable skill, not just a topic.

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Step 3 — Format & Delivery Design

We select and build the delivery format that matches organizational reality: self-paced online for scale and flexibility, instructor-led cohort for depth and accountability, or CoE-in-a-Box for enterprises building internal capability. For government and African programs, we integrate bootcamp and hackathon formats that create peer networks alongside individual capability.

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Step 4 — Facilitation & Delivery

MWH's instructors are practitioners — people who have built AI systems, led digital transformations, and solved the problems the training addresses. For university programs delivered through the AtkCo JV, we work alongside faculty to combine institutional credibility with practitioner depth. For corporate programs, we embed alongside internal L&D teams rather than parachuting in as external vendors.

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Step 5 — Capability Transfer & Sustainability

Programs are designed to run without MWH after the initial delivery cycle. For CoE-in-a-Box engagements, this includes internal trainer certification, curriculum update protocols, and governance playbooks. For government programs, we embed training-of-trainers components that multiply reach. The measure of success is not completions — it is whether the capability persists and compounds.

What You Get

  • Role-specific AI curricula** designed for five distinct audiences: STEM students (advanced AI/ML), non-STEM students (AI for their discipline), corporate L&D (digital transformation skills), faculty (AI in teaching), and government teams (public sector AI applications) - **Three delivery formats — self-paced online, instructor-led cohort, and CoE-in-a-Box — selected and configured for your organizational model
  • University-grade curriculum frameworks** developed through the AtkCo JV, with academic institution relationships and accreditation pathway support - **Practitioner instructors** with leadership DNA from Google, Square, Paramount, Uber, and Export Development Canada — not instructional designers building slides from research papers - **Government capacity-building programs** including bootcamps, hackathons, and university partnerships, with training-of-trainers built in for sustainability - **MWH Internship Program** integration for academic partners — real project experience on live client mandates, not simulated case studies - **Capability transfer documentation — every program includes the materials, governance, and internal trainer frameworks needed to sustain the program independently

Results

Case Study Callout

Chevron & Texaco — Digital Transformation Academies

MWH designed and embedded digital transformation academies directly within Chevron and Texaco's enterprise L&D infrastructure. These were not external training events — they were integrated into the organizations' existing learning architecture, aligned to role-specific transformation priorities, and built to run at scale without continuous MWH involvement. This is the model for enterprise AI training that actually changes operational behavior.

Southern University AI Program — AtkCo JV

Through the AtkCo joint venture, MWH is involved in the design and delivery of an AI program at Southern University (USA). This program brings practitioner-built curriculum into an accredited academic context — giving students AI education built around what enterprise AI actually requires, not what academic AI research prioritizes. The AtkCo JV model is designed to replicate across additional institutions.

Government Capacity Building — Africa

MWH has delivered government-facing AI and digital capacity-building programs across African markets, combining bootcamp formats, university partnerships, and hackathon models that create both individual skills and community networks. These programs are designed for contexts where instructor scarcity is a real constraint — which is why training-of-trainers and self-sustaining formats are built into the architecture from the start.

Who It's For

MWH's L&D practice serves organizations that need training to change behavior, not check a box. Ideal clients include enterprises undergoing digital transformation who need their workforce to use AI as a production tool rather than a novelty; universities seeking to build or modernize AI curricula that are informed by industry practice; governments in emerging markets building public sector digital capacity; and executive teams who need to understand AI at a strategic level — what it can and cannot do, where it creates competitive advantage, and how to govern it without stifling it. If your current training program is generating completion metrics but not capability metrics, this is the conversation to have.

Frequently Asked Questions

Q: What's the difference between your corporate bootcamp and a CoE-in-a-Box engagement?

A corporate bootcamp is a defined, time-bounded training program — typically delivered as a cohort over days or weeks — designed to bring a team to a specific capability level on a specific set of AI/ML skills. CoE-in-a-Box is a broader engagement that builds the organizational infrastructure for ongoing AI capability: curriculum library, internal trainer certification, governance playbooks, tooling frameworks, and operating model. Bootcamps build skills. CoE-in-a-Box builds the machine that keeps building skills.

Q: How does the AtkCo JV work, and what does it mean for a university considering a partnership?

The AtkCo joint venture is a formal collaboration between MWH and AtkCo focused on AI curriculum development and academic institution partnerships. For universities, this means access to curriculum frameworks built by AI practitioners — not adapted from textbooks — with support for accreditation pathway development, faculty enablement, and ongoing curriculum currency as the AI landscape evolves. The Southern University program is the live proof of concept for this model.

Q: Can you train non-technical employees on AI without overwhelming them?

Yes — and this is a design priority, not an afterthought. Non-STEM curricula are built around discipline-specific AI applications: what AI means for marketing, operations, HR, legal, finance, or supply chain — not what AI is in the abstract. Learners leave understanding where AI creates leverage in their specific role and how to work alongside AI tools without needing to understand the underlying model architecture. The goal is confident, practical fluency — not engineering knowledge.

Q: How do you handle training for organizations in markets with limited digital infrastructure?

For African government programs and similar contexts, we design with infrastructure constraints as a first-order variable, not an afterthought. This includes offline-capable content formats, mobile-first delivery design, reduced-bandwidth video optimization, and bootcamp/in-person formats that reduce dependency on connectivity. We also embed train-the-trainer components so that after MWH's direct involvement ends, local facilitators can deliver the program in contexts where external instructors cannot reliably reach.

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