
This course will give you an idea of what to expect as you progress through the courses on this site. Make sure you start here before you do anything else.
- Teacher: Dennis Salguero
This course will give you an idea of what to expect as you progress through the courses on this site. Make sure you start here before you do anything else.
In this course we will discuss some of the top principles that should guide you throughout your entire data science career
Any serious study of data science has to begin with numbers and what they mean. This builds the foundation for everything else that you will learn in these courses.
Now that we know a little bit about numbers, the next thing to learn is the basics of statistics. Statistics still drive a lot of modern data science and understanding these concepts is critical for success.
Analytics are an important part of the data science environment. In this course we will take a look at the basics of analytics and how they are still used in the business world.
Data science is not code, it is not math, it is not AI. Data science, at core, is a process. In this course we will look at the methodology that drives data science and how it should drive your thoughts and projects.
Statistics are a critical part of data science. No school would be complete if I only offered a single statistics course. In this course, we will take our statistics study to another level and look at some advanced concepts that are still very relevant in modern data science.
Make no mistake about it, machine learning is still a big part of data science and most business problems don't need to go beyond these algorithms. In this course I will introduce the essential concepts that are required for machine learning.
Neural networks can take your data science practice to an entirely new level. In this course I will discuss the basics of working with neural networks and how to implement them to solve complex problems.
Data science projects can have unique elements that need to be considered during the project planning phases. In this course we will look at some of the adjustments that need to be made when working on a data science project
Algorithms - no matter how they are developed - can have unique deployment needs. In this course we will take a look at some of those requirements and how we can work with them.
Data scientists will need to have continuous conversations with their stakeholders. In this course we will look at some of the conversations that need to take place and how you can involve your stakeholders in projects.
Data scientists are much more than just coders or math wizards. They also need to have some soft skills to survive. In this course we will look at some of those soft skills and how to start developing them.
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