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Intro to Machine Learning – Udacity

Udacity
0-6 Month Online
Intermediate Contact Institute
Online Big Data
Online Self Paced 697
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Machine Learning is a first-class ticket to the most exciting careers in data analysis today. As data sources proliferate along with the computing power to process them, going straight to the data is one of the most straightforward ways to quickly gain insights and make predictions.

Machine learning brings together computer science and statistics to harness that predictive power. It’s a must-have skill for all aspiring data analysts and data scientists, or anyone else who wants to wrestle all that raw data into refined trends and predictions.

In this course, you’ll learn by doing! We’ll bring machine learning to life by showing you fascinating use cases and tackling interesting real-world problems like self-driving cars. For your final project you’ll mine the email inboxes and financial data of Enron to identify persons of interest in one of the greatest corporate fraud cases in American history.

When you finish this introductory course, you’ll be able to analyze data using machine learning techniques, and you’ll also be prepared to take our Data Analyst Nanodegree. We’ll get you started on your machine learning journey by teaching you how to use helpful tools, such as pre-written algorithms and libraries, to answer interesting questions.

Course Contents

  • Lessons 1-4: Supervised Classification
  • Lesson 5: Datasets and Questions
  • Lesson 6 and 7: Regressions and Outliers
  • Lesson 8: Unsupervised Learning
  • Lessons 9-12: Features, Features, Features
  • Lessons 13-14: Validation and Evaluation
  • Lesson 15: Wrapping it all Up

Projects

Mini-project at the end of each lesson

Final project: searching for signs of corporate fraud in Enron data

Duration:

10 weeks

Assumes 6hr/wk (work at your own pace)

Fee: INR 11,940/Month (assuming $ = INR 60)

  • To succeed in this course, you must be proficient at programming in Python, basic statistics, and data science.
  • One thing that we don’t require is previous exposure to machine learning. If you’re a machine learning beginner, you’re in the right place.
  • Sebastian Thrun
  • Katie Malone
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