4 Must-Take Advanced Mathematics Courses for Data Science Wizards!

The rise of the internet and accessibility of massive data has led to today’s data driven approach further leading to creation of machine learning models. Many of today's leading companies, such as Facebook, Google and Uber, make machine learning a central part of their operations and it has become a significant competitive differentiator for many companies.?

This list article provides all the required information on the most effective beginner-level Mathematics for Data Science certification courses.?

Introduction to Mathematics for Data Science

Mathematics is an integral part of data science. Any practicing data scientist or person interested in building a career in data science will need to have a strong background in specific mathematical fields.?

Math is a core educational pillar for data scientists, regardless of your future industry career path. It ensures you can help an organization solve problems and innovate more quickly, optimize model performance, and effectively apply complex data towards business challenges.

Top Advanced level Mathematics for Data Science skills?

The major skills covered include theoretical basics, teaching you about the software and its applicability, and the technical skills needed. These are as follows:

TensorFlow

TensorFlow is an open-source software library developed by Google to conduct machine learning and deep neural networks research. It makes it easier for beginner-level professionals to create machine learning models for mobile, desktop, web and cloud.?

Deep Learning Techniques

Deep learning is machine learning that learns to perform classification tasks by analyzing images, text, or sound. The models are trained with a large set of labeled data and neural network architectures containing many layers.?

NLP

Natural language processing is a field of computer science and AI that focuses on understanding and processing the interactions between computers and natural human languages. Specialists leverage NLP technologies to process natural language data efficiently, performing tasks like speech recognition for various industries.?

Top Mathematics for Data Science Learning Platforms

There are multiple learning platforms providing courses on Mathematics for Data Science. Some of them are listed below-

• Coursera: It collaborates with more than 200 leading companies and universities to provide world-class training and development programs to individuals all across the globe.
• Eduonix- It is a skill development organization that provides for online degrees and certifications. Their aim is to bring world class training content and best learning practices to every learner across the globe.

Advanced Mathematics for Data Science courses

Advanced Linear Models for Data Science 1: Least Squares

• The course will give you the basic understanding of multivariate calculus and linear algebra including statistics, regression models and other statistical concepts.

• Pedagogy- This self paced course is 8 hours long and provides you with instructor-moderated discussions and post course interactions.
• Instructor- The course instructor, Brian Caffo, PhD is a professor in the Department of Biostatistics at the Johns Hopkins University Bloomberg School of Public Health.?
• Hands on approach- This course offers the learners hands-on training and interaction with international faculty.
• Price- You can join this course for
• ?459/mo
• $17/mo
• ￡14/mo

Probabilistic Deep Learning with TensorFlow 2

• This course is on Probabilistic Deep learning with TensorFlow and focuses on deep learning using probabilistic methods.
• Instructor- The course instructor, Kevin Webster is a Senior Teaching Fellow in the Department of Mathematics at Imperial College London. He obtained his PhD from Imperial College in the field of dynamical systems.?
• Pedagogy- This self paced course is 53 hours and provides you with case studies, instructor-moderated discussions and post course interactions.
• Hands on approach- The course offers hands-on training, virtual labs, classes from the international faculty and capstone project at the end.?
• Price- You can join this course for
• ?1,727/mo
• $21/mo
• ￡18/mo

Advanced Linear Models for Data Science 2: Statistical Linear Models

• The course will provide a solid foundation in linear algebraic regression modeling after taking this course. It will enhance the knowledge of applied data scientists about regression models.
• Instructor- The course instructor, Brian Caffo, PhD is a professor in the Department of Biostatistics at the Johns Hopkins University Bloomberg School of Public Health.?
• Pedagogy- The course is self paced and is of 6 hours duration. It provides instructor moderated discussions and post course interactions to the learners.?
• Price- You can join this course for
• ?917/mo
• $17/mo
• ￡14/mo

AI Workflow: Data Analysis and Hypothesis Testing

• As part of this course, you will learn best practices for data visualization, handling missing information, and hypothesis testing. These techniques will allow you to estimate probability distributions, and then extend these estimates to use null hypothesis significance tests.
• Instructor- The course instructor, Mark J. Grover is a member of the IBM Data & AI Learning team and specializes in creating and delivering online content.
• Pedagogy- This instructor paced course is of 11 hours duration and provides you with instructor-moderated discussions and post course interactions.
• Hands on approach- The course offers case based learning and classes from the international faculty.
• Price- You can join this course for
• ?1,856/mo
• $34/mo
• ￡28/mo

Final Thoughts

In today's data-driven landscape, machine learning stands as a pivotal force shaping industries worldwide. Companies like Facebook, Google, and Uber leverage its power, underscoring its competitive edge. Mathematics lays the groundwork for data science, empowering practitioners to navigate complex algorithms and drive innovation. From beginner to advanced levels, courses on platforms like Coursera and Eduonix offer comprehensive insights into TensorFlow, deep learning, and NLP. These courses, guided by esteemed instructors, equip learners with essential skills, fostering a hands-on approach vital for success in the dynamic field of data science.