Machine Learning (AI) Engineer Work Experience Certification Course Program

The most advanced and latest machine learning course program! Through three months of mentor guided work experiences in Machine Learning Engineer, you will learn, grow and be evaluated in full stack machine learning abilities.

Participants join our Machine Learning Engineer work experience program around the world for 12 weeks (3 months), throughout the year, to work in teams. Successfully completing this Machine Learning Engineer program within the stipulated time will ensure that you can demonstrate your competence as a Machine Learning Engineer and meet real world expectations. This work experience offers you a Machine Learning Engineer certification that is greatly valued by hiring managers.

When you join Savio Global in this simulation of a Machine Learning Engineer, you are joining a firm that will challenge you and ensure your professional development. In this role you will work on the best teams to solve difficult business problems and perform professional Machine Learning Engineer. You will also work with many experts, from data scientists and researchers to software and app designers.

Your Machine Learning Engineer Work Experience

You’ll work in teams of typically 3 – 5 professionals, playing an active role in all aspects of the engagement.

In this Machine Learning Engineer program, you will perform the role of a Machine Learning Engineer, which includes gathering and analyzing data, training the latest machine learning models, assessing model performance, optimizing models and productionizing them on the cloud.

Our Machine Learning Engineer Work Experience program gives students first-hand experiences. Through this course, you will participate in continuous training, as well as a range of continuous learning activities to get to know your work leading up to your Machine Learning Engineer certification.

Duration

12 weeks (3 months)

Batches and Times

A new batch begins every Monday. The cohort meets online (Google Meet) every Thursday and Saturday at a time convenient for all participants.

Your Learning

You’ll gain new skills and build on the strengths you may already have. You as a Machine Learning Engineer will receive exceptional training as well as frequent coaching and mentoring from colleagues on your teams. This support includes daily training. Moreover, to ensure that you are a truly certified Machine Learning Engineer professional, an expert from our practice is assigned to you to help guide you throughout your work experience.

Through two months of mentor guided work experiences in Machine Learning Engineer, you will learn, grow and be evaluated in full stack machine learning abilities like:

Module 1

• acquire data from file and API data sources
• perform exploratory data analysis and visualization
• create and setup data processing pipelines

• Details:
  • reading data from csv, excel and json files
  • combining datasets from multiple sources
  • reading data from APIs
  • structuring / formatting data for use
  • encoding and processing data into machine readable numerical form
  • chaining multiple steps together for ease of data administration
  • deriving knowledge from statistical analysis like correlations and central tendencies
  • visualizing data and presenting insights

Module 2

• understand and select appropriate machine learning models for different business situations
• train machine learning models
• measure model performance
• Optimize machine learning models to deliver the best performance

• Details:
  • Train regression and classification supervised learning models - intuition and programming with Python
    • Linear regression
    • Logistic regression
    • K nearest neighbors (KNN)
    • Decision trees
    • Support vector machines (SVM)
  • Evaluate model performance using mean absolute error, mean squared error, root mean squared error, accuracy, precision, recall, F1 score, etc.
  • Perform feature engineering and selection to improve model performance

Module 3

• Understand and select appropriate machine learning models for different business situations
• Train ensemble supervised learning models
• Measure model performance
• Optimize machine learning models to deliver the best performance

• Details:
  • Train ensemble supervised learning models - intuition and programming with Python
    • Bagged trees
    • Random forests
    • Adaptive boosted trees
    • Gradient boosted trees + Extreme gradient boosted trees
    • Perform hyperparameter tuning to further optimize the model

Module 4

• Train unsupervised learning models - intuition and programming with Python
• Train deep learning models - intuition and programming with Python
• Create multiple machine learning apps!

• Details:
  • K-means clustering
  • Hierarchical clustering
  • DBSCAN
  • Recurrent neural network
  • Convolutional neural network
  • Transformers!
  • Demonstrate your models to non-technical stakeholders

Module 5

• Use multiple deployment strategies to serve these machine learning models in the cloud
• Bonus: perform ML engineering with Google Cloud Platform (GCP) Vertex AI and Cloud Run!

Module 6

• Perform advanced natural language processing and understanding
• Utilize large language (LLM) generative AI models: text to text and text to image
• Perform computer vision tasks like object recognition

4 hours live sessions every week!

All live session with industry experts!

Create a credible portfolio of apps and your work to showcase to prospective recruiters and hiring managers!

Our participants work at the best companies worldwide

Meet your Mentor

Savio serves as the Vice President for data sciences and AI in the Asia-Pacific region at dentsu. His extensive background and cross functional expertise in web technology, AI and project and product management allows him to build great teams that get the job done.
He loves to teach too, has taught over 2000 professionals and is regularly invited to speak at technology conferences and as a visiting faculty to global universities.
Ex-TCS-Bank of America, L&T FSTI.
Contributing Author to the Project Management Standard Seventh Edition, PMI USA.
Top 5% in AI ML globally recognized by LinkedIn.
Advisor, Harvard Business Review Council, USA.
Contributing Member, Python Software Foundation, USA.
Partner Member, Neo4j NoSQL Graph Database, UK.
Certified Tableau Professional – Consumer, Author, Designer, Tableau Software USA.
Certified Alteryx Designer, Alteryx USA.
Certified Project Management Instructor, PMI USA.
Certified Software Quality Assurance Specialist, ISTQB Belgium.
Connect on LinkedIn

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Includes over 50 hours of instructional videos for FREE!
Placement assistance included. Know more here.

This low cost, high value Machine Learning Engineer experience provides you a Machine Learning Engineer certification and prepares you and enhances your skills to secure a job as a Machine Learning Engineer. Explore thousands of Machine Learning Engineer Jobs (Credly: External Site).

Tools

You will learn and work with several modern ML tools such as:

• Sci-kit Learn,
• PyTorch,
• Numpy,
• Seaborn,
• Plotly,
• Pandas,
• Streamlit,
• FastAPI, and
• Google Cloud Platform (GCP) using Python.

Extensions

The program is flexible, and participants may take up to two weeks off during the program.

We look forward to you joining us!

Frequently asked questions about the Machine Learning Engineer Work Experience program

• What is the duration of the Machine Learning Engineer work experience program?The program is 12 weeks long, equivalent to 3 months.
• When does the Machine Learning Engineer work experience program start?A new batch begins every Monday, and the cohort meets online (Google Meet) every Tuesday, Thursday, and Saturday at a time convenient for all participants.
• What will I do during the Machine Learning Engineer work experience program?As a participant in the Machine Learning Engineer work experience program, you will work in teams of typically 3-5 professionals, playing an active role in all aspects of the engagement. You will perform the role of a Machine Learning Engineer, which includes gathering and analyzing data, training machine learning models, assessing model performance, optimizing models, and productionizing them on the cloud. You will also work with experts from various fields, including data scientists, researchers, software designers, and app designers.
• What skills will I gain from this Machine Learning Engineer work experience program?Through the program, you will gain skills in full-stack machine learning, including acquiring data from file and API data sources, setting up data processing pipelines, selecting appropriate machine learning models for different business situations, training machine learning models, optimizing machine learning models for performance, creating machine learning apps, and deploying machine learning models in the cloud using various strategies, including Google Cloud Platform (GCP) Vertex AI and Cloud Run.
• Will I receive any certification after completing the Machine Learning Engineer work experience program?Yes, upon successfully completing the Machine Learning Engineer work experience program, you will receive a Machine Learning Engineer certification and badge that is greatly valued by hiring managers. You will also have the opportunity to create a credible portfolio of apps and your work to showcase to prospective recruiters and hiring managers.
• Who will be my mentor during the Machine Learning Engineer work experience program?Your mentor during the program will be Savio Saldanha, who serves as the Vice President for data sciences and AI in the Asia-Pacific region at dentsu. Savio has extensive background and cross-functional expertise in web technology, AI, project and product management, and is regularly invited to speak at technology conferences. He will provide coaching and mentoring to help guide you throughout your work experience.
• What tools will I learn and work with during the Machine Learning Engineer work experience program?During the program, you will learn and work with several modern machine learning tools, including Sci-kit Learn, PyTorch, Numpy, Seaborn, Plotly, Pandas, Streamlit, FastAPI, and Google Cloud Platform (GCP) using Python.
• Is there any flexibility in the program schedule?Yes, the program is flexible, and participants may take up to two weeks off during the program.
• Is placement assistance included in the program?Yes, placement assistance is included in the program, and you can explore thousands of machine learning engineer jobs through the Credly site.
• What are the benefits of completing the Machine Learning Engineer work experience program?Successfully completing the program will enable you to demonstrate your competence as a Machine Learning Engineer and meet real-world expectations. You will receive a Machine Learning Engineer certification, gain new skills, build on your strengths, and create a credible portfolio of apps and work to showcase to prospective recruiters and hiring managers, enhancing your chances of securing a job as a Machine Learning Engineer.
• Can I participate in the program from anywhere in the world?Yes, the program is open to participants from around the world, and you can join from anywhere.