Custom Machine Learning Learning Programs

Finding a consultative ML learning partner to design and execute effective learning strategies shouldn't be so hard.

Current Tech Landscape

The world of tech learning has changed. Our team is constantly reviewing the tech landscape in an effort to help our partners learn the latest strategies and be at the forefront of the next tech.

We fundamentally believe there needs to be a new way, a modern way, to upskill, reskill, and transform the innovators, technologists, and developers who are creating the next generation of technologies.

We focus on providing an encompassing view of the tech marketplace and key strategies to help funded organizations drive employee engagement and bottom-line growth.

94%

of employees would stay longer in companies that are willing to invest in their professional development.

68%

of employees prefer to learn or train in the workplace to grow their skills.

80%

of tech budgets are spent on optimizing existing business capabilities and augmenting capabilities with new capabilities.

Our Philosophy

CONSUMABLE

ILT is delivered in consumable chunks within daily workflows

SUPPORTED

Self-paced, pre and post-work and office hours through the experience. No one is left behind

CUSTOMIZED

Every program is customized to your team, the stack, and the desired outcome

REAL WORLD

Practical learning through real-world projects, capstones, and live coding increase adoption cycle

MEASUREABLE

True measurement before and after the program to determine skill gain and where additional support is needed

Machine Learning Sample Topics

Leveraging Machine Learning in Data Engineering

Data Lakes vs. Data Warehouses: Choosing the Right Architecture

Advanced ETL Processes and Tools

Securing Your Data Infrastructure: Best Practices and Technologies

Big Data Technologies: Hadoop and Beyond

Streamlining Data Pipelines: Best Practices and Optimization Techniques

Sample Learning Journey Structure

Curated Self-Paced Learning

Knowledge Checks

ILT - miniBilt or simplyBilt format

Curated Self-Paced Learning

Knowledge Checks

ILT - miniBilt or simplyBilt format

Curated Self-Paced Learning

Knowledge Checks

ILT - miniBilt or simplyBilt format

Curated Self-Paced Learning

Knowledge Checks

ILT - miniBilt or simplyBilt format

Sample Program: Machine Learning

PROGRAM OVERVIEW
The Machine Learning Foundations customBILT rapidly advances Python developers to Machine Learning experts, focusing on real-world problem-solving through key practices like data preprocessing and model deployment. Through intensive hands-on exercises and projects, participants utilize major ML libraries—Scikit-learn, TensorFlow, PyTorch—to build and deploy advanced models.

View Full Program

Audience
Software Engineers with some Python exposure.

Intended Outcome
Deep Learning Solutions in main areas of Deep Learning, Natural Language Processing, and Reinforcement Learning.

Easy path to get started.

1. Tell us about your project needs

Meet with us and we'll review your overall team needs.

2. We design a custom learning solution

Working with your stakeholders, we'll collaborate on a win-win solution.

3. Approve the custom, blended learning solution

After approving the solution, we'll decide on a mutually beneficial timeframe.

4. We resource, build and manage

Get matched with a technical solution expert to build the entire solution.

5. We pilot the solution

And we're focusing on measuring impact and ROI.

6. We adjust and improve

The goal is continuously improving the impact and ROI over the transformation effort.

Check out our latest tech learning resources.

Machine Learning Full Program

View a sample program build out of our full program, including weekly program work and learning topics for your team.

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5 Reasons ILT Courses Alone Won't Work

If companies use just instructor led training (ILT) courses, there's a big chance that the desired outcomes won't be met after course completion.

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5 Reasons Self-Paced Libraries Fall Short

Many companies rely mostly on self-paced libraries and SaaS platforms for their tech teams. We review five key reasons why this doesn't always work.

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