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Data Science

Machine Learning and AI Foundation

Group Training + View more dates & times 

                 

                
                        Overview
                        

                            

Learn to take your solutions to the next level by harnessing the power of data in Machine Learning Foundation, a 3-day instructor-led course tailored for tech professionals. This comprehensive program covers essential topics, including the principles of machine learning, model development and evaluation strategies, as well as techniques for processing and understanding data. Gain hands-on experience with machine learning toolkits such as PyTorch, Scikit-Learn, Polars, NumPy and Plotly. Prerequisites include intermediate programming skills, mathematics foundation, data analysis familiarity, and a willingness to review pre-course materials. Elevate your skills and analyze data and build machine learning solutions. Enroll today to advance your career and stay competitive in the ever-evolving field of Machine Learning.





Duration





3 Days

                        

                

                                            

                        
                            Who Should Take This Course
                            

                                
AUDIENCE


Developers, Data Engineers, IT and QA Staff, Technical Managers, DevOps Engineers, Analysts, Project Managers.


Prerequisites


Participants should have beginner programming skills (preferably in Python), a foundational understanding of mathematics and statistics, experience with data analysis using tools like Pandas, a grasp of computer science fundamentals, familiarity with common operating systems and basic command-line operations, and a willingness to review pre-course materials.


These prerequisites will help participants engage effectively with the course material and hands-on labs, making the learning experience more rewarding. Attendees will also need to be able to ssh into a supplied cloud instance during the course to complete the lab work.

                            

                    

                                                                

                        
                            Why You Should Take This Course
                            

                                
Upon completing this course, participants will be able to:


    

  • Understand the fundamental concepts of machine learning and how they’re applied to provide value
    • 

  • Learn how to develop, tune and test machine learning models
    • 

  • Become familiar with tools for machine learning and data analysis
    • 

  • Gain insight into how production grade machine learning solutions are developed
    • 

  • Acquire hands-on experience building models and solving problems with ML
    • 

  • Learn insights from industry veterans about how to develop successful ML projects
    • 

  • Develop the skills and understanding to develop deep learning solutions
    • 


                            

                    

                                                                                

                    
                        Schedule
                        

                            
                            
                            
                            

                        

                    

                                                            

                    
                        Course Outline
                        

                            
Day 1: Fundamentals


    

  1. 

      

    1. Machine Learning Overview
      2. 

    2. Data Processing with NumPy and Pandas
      3. 

    3. Data Preparation
      4. 

    4. Data Visualization and Exploratory Data Analysis
      5. 

    

    2. 



Day 2: Machine Learning Models


    

  1. 

      

    1. Measuring Models – Losses and Metrics
      2. 

    2. Linear Models
      3. 

    3. Nonlinear Models: Supervised
      4. 

    4. Nonlinear Models: Unsupervised
      5. 

    

    2. 



Day 3: Deep Learning


    

  1. 

      

    1. Hyperparameter Tuning and Experimentation
      2. 

    2. Deep Learning Fundamentals
      3. 

    3. Training Neural Networks
      4. 

    4. Building Deep Learning Models with PyTorch
      5. 

    

    2. 


                        

                    

                                                            

                    
                        FAQs
                        

                            
Is there a discount available for current students?


UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.


What is the cancellation and refund policy?


Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.

                        

                    

                                                            

            

            
        

    

    







    


    











				









    

      

        
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