Applied Data Science with Python
4.0 (110 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
2,462 students enrolled
Wishlisted Wishlist

Please confirm that you want to add Applied Data Science with Python to your Wishlist.

Add to Wishlist

Applied Data Science with Python

Learn how to execute an end-to-end data science project and deliver business results
4.0 (110 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
2,462 students enrolled
Created by V2 Maestros, LLC
Last updated 1/2017
English
Current price: $10 Original price: $100 Discount: 90% off
4 days left at this price!
30-Day Money-Back Guarantee
Includes:
  • 8.5 hours on-demand video
  • 2 Articles
  • 2 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Appreciate what Data Science really is
  • Understand the Data Science Life Cycle
  • Learn to use Python for executing Data Science Projects
  • Master the application of Analytics and Machine Learning techniques
View Curriculum
Requirements
  • Programming experience in Python
  • Experience in analyzing Data preferred
Description

"Data Science is the sexiest job of the 21st century - It has exciting work and incredible pay".

Learning Data Science though is not an easy task. The field traverses through Computer Science, Programming, Information Theory, Statistics and Artificial Intelligence. College/University courses in this field are expensive. Becoming a Data Scientist through self-study is challenging since it requires going through multiple books, websites, searches and exercises and you will still end up feeling "not complete" at the end of it. So how do you acquire full-stack Data Science skills that will get you a and give you the confidence to execute it?

Applied Data Science with Python addresses the problem. This course provides extensive, end-to-end coverage of all activities performed in a Data Science project. If teaches application of the latest techniques in data acquisition, transformation and predictive analytics to solve real world business problems. The goal of this course is to teach practice rather than theory. Rather than deep dive into formulae and derivations, it focuses on using existing libraries and tools to produce solutions. It also keeps things simple and easy to understand.

Through this course, we strive to make you fully equipped to become a developer who can execute full fledged Data Science projects. By taking this course, you will

  • Appreciate what Data Science really is
  • Understand the Data Science Life Cycle
  • Learn to use Python for executing Data Science Projects
  • Master the application of Analytics and Machine Learning techniques
  • Gain insight into how Data Science works through end-to-end use cases.

By becoming a student of V2 Maestros, you will also get maximum discounts on all of our other current and future courses (coupon codes inside the course material). You will also get prompt support of all your queries and questions. We continuously strive to improve our course material to reflect the latest trends and technologies

Who is the target audience?
  • IT Professionals aspiring to be Data Scientists
  • Students who want to learn about Data Science domain
  • Statisticians and Project Managers who want to expand their horizon into Data Science
Students Who Viewed This Course Also Viewed
Curriculum For This Course
44 Lectures
08:16:56
+
Introduction
3 Lectures 12:28
+
What is Data Science?
5 Lectures 52:48
Basic Elements of Data Science
11:51

The Dataset
10:44


Modeling and Prediction
09:31

Use Cases for Data Science
07:47
+
Data Science Life Cycle
3 Lectures 42:59
Stage 1 - Setup
11:46

Stage 2 - Data Engineering
11:57

Stage 3 & 4 - Analysis and Production
19:16
+
Statistics for Data Science
4 Lectures 52:53
Types of Data
07:29

Summary Statistics
16:10

Statistical Distributions
19:05

Correlations
10:09
+
Python for Data Science
3 Lectures 42:03
Python libraries Overview
16:42

Examples 1 - Series and Data Frames
16:28

Examples 2 - Grouping and Graphics
08:53
+
Data Engineering
5 Lectures 01:02:04
Data Acquisition
16:01

Data Cleansing
10:50

Data Transformations
11:09

Text Preprocessing TF-IDF
14:53

Python examples for Data Engineering
09:11
+
Machine Learning and Predictive Analysis
15 Lectures 03:16:25

Types of Learning
17:16

Analyzing results and errors
13:46

Linear Regression
19:00

Python Use Case : Linear Regression
18:44

Decision Trees
10:42

Python Use Case : Decision Trees
15:21

Naive Bayes Classifier
19:21

Python Use Case : Naive Bayes
06:50

Random Forests
10:31

Python Use Case : Random Forests
12:17

K-Means Clustering
11:53

Python Use Case : K-Means Clustering
09:36

Association Rules Mining
11:31

Python Use Case : Association Rules Mining
07:29
+
Advanced Topics
4 Lectures 31:09
Artificial Neural Networks and Support Vector Machines
04:35

Bagging and Boosting
11:27

Dimensionality Reduction
07:28

Python Use Case : Advanced Methods
07:39
+
Conclusion
2 Lectures 04:07
Closing Remarks
04:02

BONUS Lecture : Other courses you should check out
00:05
About the Instructor
V2 Maestros, LLC
4.2 Average rating
2,566 Reviews
25,915 Students
13 Courses
Big Data Science / Analytics Experts | 25K+ students

V2 Maestros is dedicated to teaching big data / data science at affordable costs to the world. Our instructors have real world experience practicing big data and data science and delivering business results. Big Data Science is a hot and happening field in the IT industry. Unfortunately, the resources available for learning this skill are hard to find and expensive. We hope to ease this problem by providing quality education at affordable rates, there by building data science talent across the world.