Über diesen Kurs

This course will teach you how to start from scratch in answering questions about the real world using data. Machine learning happens to be a small part of this process. The model building process involves setting up ways of collecting data, understanding and paying attention to what is important in the data to answer the questions you are asking, finding a statistical, mathematical or a simulation model to gain understanding and make predictions.

All of these things are equally important and model building is a crucial skill to acquire in every field of science. The process stays true to the scientific method, making what you learn through your models useful for gaining an understanding of whatever you are investigating as well as make predictions that hold true to test.

We will take you on a journey through building various models. This process involves asking questions, gathering and manipulating data, building models, and ultimately testing and evaluating them.

Kursgebühren
Kostenlos
Zeitachse
Ca.8weeks
Niveau
Profis
Vorteile

Rich Learning Content

Interactive Quizzes

Taught by Industry Pros

Self-Paced Learning

Student Support Community

Begib' dich auf den Weg des Erfolgs

Dieser kostenlose Kurs ist der erste Schritt auf dem Weg zu einer neuen Karriere mit dem Machine Learning Engineer Programm.

Kostenlose Kurse

Modellerstellung und -validierung

mit AT&T

Erweitere deine Fähigkeiten und Karriere durch innovatives und unabhängiges Lernen.

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Tutoren

Don Dini
Don Dini

Tutor

Rishi Pravahan
Rishi Pravahan

Tutor

Was du lernst

Voraussetzungen

This is an Profis course, and the ideal students for this class are prepared individuals who have:

  1. Python programming knowledge, familiarity with python tools like Ipython Notebook and data analysis libraries like Scikit-learn, Scipy, and Pandas
  2. Knowledge of descriptive, inferential, and predictive statistics
  3. Knowledge of calculus, especially derivatives and integrals
  4. Knowledge of basic matrix algebra - matrices, vectors, determinant, identity matrix, multiplication, inverse
  5. Taken Intro to Machine learning and have understanding of common supervised learning and unsupervised learning algorithms, such as SVM and k-means clustering

Detaillierte technische Voraussetzungen

Was spricht für diesen Kurs?

Many of you may have already taken a course in machine learning or data science or are familiar with machine learning models.

In this course we will take a more general approach, walking through the questioning, modeling and validation steps of the model building process.

The goal is to get you to practice thinking in depth about a problem and coming up with your own solutions. Many examples we will attempt may not have one correct answer but will require you to work through the problems applying the methods we hope to illustrate throughout this class.

Was bekomme ich?
Instructor videos Learn by doing exercises Taught by industry professionals