Applied Data Science with Python

Learn how to execute an end-to-end data science project and deliver business results
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  • Lectures 44
  • Contents Video: 8.5 hours
    Other: 0 mins
  • Skill Level Intermediate Level
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android
    Certificate of Completion
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About This Course

Published 3/2015 English

Course 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

What are the requirements?

  • Programming experience in Python
  • Experience in analyzing Data preferred

What am I going to get from this course?

  • 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

What 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

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.

Curriculum

Section 1: Introduction
About this course
Preview
10:48
About V2 Maestros
Preview
01:39
Resource Bundle
Article
Section 2: What is Data Science?
Basic Elements of Data Science
11:51
The Dataset
10:44
Learning from relationships
Preview
12:55
Modeling and Prediction
09:31
Use Cases for Data Science
07:47
Section 3: Data Science Life Cycle
Stage 1 - Setup
11:46
Stage 2 - Data Engineering
11:57
Stage 3 & 4 - Analysis and Production
19:16
Section 4: Statistics for Data Science
Types of Data
07:29
Summary Statistics
16:10
Statistical Distributions
19:05
Correlations
10:09
Section 5: Python for Data Science
Python libraries Overview
16:42
Examples 1 - Series and Data Frames
16:28
Examples 2 - Grouping and Graphics
08:53
Section 6: Data Engineering
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
Section 7: Machine Learning and Predictive Analysis
Types of Analytics
Preview
12:08
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
Section 8: Advanced Topics
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
Section 9: Conclusion
Closing Remarks
04:02
BONUS Lecture : Other courses you should check out
Article

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Instructor Biography

V2 Maestros, Big Data Science / Analytics Experts | 10K+ 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.

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