Machine Learning Fundamentals: Statistics, Probability, and Bistromathematics with Advanced Workshop
Applied Mathematics and Algorithms in Data Science.
GK# 7604
Applied Mathematics and Algorithms in Data Science.
GK# 7604
Statistics, Probability, and BistroMathematics is a primer on the mathematics and algorithms used in Data Science and creating the mathematical foundation and building the intuition necessary for solving complex machine learning problems.
The course provides a solid foundation in basic terminology and concepts, extended and built upon throughout the engagement. Processes and best practices are discussed and illustrated through both discussions and group activities. Throughout the course students will be led through a series of progressively advanced topics, where each topic consists of lecture, group discussion, comprehensive hands-on lab exercises, and lab review.
This course reviews key foundational mathematics and introduces students to the algorithms of Data Science.
Students will understand:
Lesson: Calculus and Linear Algebra Review
Lesson: Statistics Review
Lesson: Probability Review
Session: Machine Learning and Algorithms
Lesson: Supervised Learning
Lesson: Unsupervised Learning
Lesson: Regression Algorithms
Lesson: Classification Algorithms
Lesson: Clustering Algorithms
Lesson: Neural Networks
Lesson: Dimensionality Reduction
Session: Best Practices and the Real World
Lesson: Ensemble Methods
Lesson: In the Real World
Skill-focused, Hands- on Learning: This class is “technology-centric”, designed to train attendees in essential skills, coupling the most current, effective techniques with the soundest industry practices. This course is about 50% hands-on lab and 50% lecture, with extensive programming exercises designed to reinforce fundamental skills and concepts learned in the lessons. Our courses include a wide range of complementary materials and labs to ensure all students are appropriately challenged or assisted at all times, no matter their incoming skill level.
This 5-day course has the students creating ground-up implementations of key mathematics and algorithms using Python, NumPy, and basic libraries for building a deeper mathematics-programming intuition.
This course is available in the following formats:
Experience expert-led online training from the convenience of your home, office or anywhere with an internet connection.