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Custom Machine Learning Learning Programs
Finding a consultative ML learning partner to design and execute effective learning strategies shouldn't be so hard.
Let’s Chat Strategy
Current Machine Learning Landscape
Despite a recent decline, machine learning remains the most in-demand AI skill, required in 0.7% of all job postings in the U.S., according to Stanford University.
Overall, insights from industry leaders indicate that 32% of executives and 38% of IT professionals believe organizations should prioritize investing in talent and training to help beginners effectively utilize AI technologies like machine learning. Additionally, 66% of employers recognize a need for upskilling in their workforce to maximize the potential of AI tools.
Notably, 97% of companies deploying AI technologies such as machine learning and generative AI have reported significant benefits, including increased productivity, improved customer service, and reduced human error.
of executives believe organizations should invest in talent and training for AI technologies.
of employers see a need for upskilling to maximize AI tool potential.
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 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.
Audience
Software Engineers with some Python exposure.
Intended Outcome
Deep Learning Solutions in main areas of Deep Learning, Natural Language Processing, and Reinforcement Learning.
ASSESSMENT
CHECK
CHECK
ASSESSMENT
FOUNDATIONS
- INTRODUCTION TO MACHINE LEARNING
- DATA PRE-PROCESSING
ADVANCED TOPICS
- SUPERVISED LEARNING - REGRESSION
- SUPERVISED LEARNING - CLASSIFICATION
- UNSUPERVISED LEARNING AND EVALUATION
REAL-WORLD APPLICATION
- INTRODUCTION TO NEURAL NETWORKS
- CONVOLUTIONAL NEURAL NETWORKS
- RECURRENT NEURAL NETWORKS AND LSTM
- REINFORCEMENT LEARNING
- MODEL DEPLOYMENT AND COURSE WRAP UP
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
We pilot and test the solution before the broad rollout.
6. We adjust and improve
The goal is continuously improving the impact and ROI over the transformation effort.