Commercial Machine Learning and Data Science Courses and Mentorship

Machine Learning

Are you a research-focused data scientist looking to bridge the gap between your data exploration skills and real-world commercial applications? I’ve crafted a comprehensive training program just for you. My program is designed to help you overcome the unique challenges of implementing industry-standard practices and technologies while translating your core R&D concepts into scalable, commercially viable solutions.

Welcome to my Data Science Training Program

In this program, I don’t just scratch the surface – I dive deep into essential concepts and provide a hands-on, practical approach. You’ll not only learn but also apply these technologies directly in the context of your current role. By the end of the training, you’ll not only be informed but also equipped to build and develop your own infrastructure, systems, and methodologies tailored to your specific responsibilities.

Essentials in AWS for Data Scientists

Databases and Infrastructure

Containerization Essentials

Essential Coding Standards for a Data Scientist/Machine Learning Engineer

Data Insights & Exploratory Analysis

Software Packaging & Deployment

Program Highlights

1. Essentials in AWS for Data Scientists

Introduction to AWS: Gain a solid understanding of the AWS ecosystem, key services, and their significance for machine learning.
Amazon Sagemaker: Dive deep into building, training, and deploying models.
Data Storage and Management: Learn to incorporate Amazon RDS, Redshift, S3, and DynamoDB in your data pipeline.
Infrastructure as Code with Terraform: Efficiently deploy and manage AWS resources.
Amazon ECS (Elastic Container Service): Master the management and creation of containerized services, understand task definitions, services, and clusters.

2. Databases and Infrastructure

Setting up in AWS: Learn to design and monitor databases in AWS, including RDS and DynamoDB.
Best practices: Discover the best practices for handling databases in both production and development environments, backing up data, and merging databases.
Understanding the use of:
- Relational Databases: Grasp SQL and efficient data retrieval.
- NoSQL Databases: Explore DynamoDB and its specific use cases.

3. Containerization Essentials

Introduction to Containers: Understand the significance and applications of containerized solutions.
Docker Deep Dive: Build Dockerfiles, manage containers, and master Docker Compose.
Container Orchestration with ECS: Deploy, scale, and ensure high availability for applications.

4. Essential Coding Standards for a Data Scientist/Machine Learning Engineer

Python Best Practices: Craft clean, efficient, and maintainable code.
Version Control with Git: Master tracking and managing code changes.
Testing and Validation: Construct unit tests and understand model validation techniques.
Code Documentation and Collaboration: Maintain clear, consistent documentation.

5. Data Insights & Exploratory Analysis

Creating Data Insights: Translate data findings into actionable business insights.
Setting up an Exploratory Data Analysis (EDA) Platform: Learn about tools, techniques, and best practices for a thorough data examination and visualization.

6. Software Packaging & Deployment

ML Ops: Grasp continuous integration and deployment for ML projects.
Model Monitoring: Learn techniques to ensure sustained model accuracy over time.
Software Packaging: Discover best practices in packaging software and dependencies for distribution and production environments.

Joe Maliszewski

About the tutor

Hi I'm Joe Maliszewski and I am passionate about the scalable applications of data science and machine learning engineering. I believe in their power to revolutionise industries, reinvent business models, and reshape the world.

My journey began in the medical and automotive sectors, where I witnessed the transformative impact of properly harnessed and scaled machine learning. This experience sparked my interest in cloud computing, a realm where I’ve deployed scalable, robust, and secure applications.

With extensive expertise in cloud computing, I’ve built and deployed scalable, robust and secure applications. It’s here, amidst the infinite possibilities of the cloud, that I discovered the true potential of machine learning and data science – the capacity to handle vast amounts of data and deliver insights of unprecedented depth and accuracy. But beyond technical mastery, my driving force is sharing this knowledge and guiding others on their journey into this exciting field.

As your mentor and tutor, my goal is to make these complex concepts tangible, accessible, and engaging. Whether you’re an aspiring data scientist, a software developer broadening your skills, or simply intrigued by AI, I’m here to guide you. Together, let’s unlock the secrets of machine learning and data science, and discover how you can leave your mark. Let’s embark on this journey together!

Don't Miss This Opportunity

Join me on this journey to enhance your data science skills and transform your insights into real-world solutions. My training program equips you with the knowledge and practical experience needed to succeed in today’s data-driven business landscape.

Enroll now and take your data science career to the next level!