Data Science For Executives 2023
Machine learning, data visualization and hands on experience.
What you'll learn
Understand what are the main concepts behind data science for different industries
Learn about the tools available for data science
Getting real hands-on experience on the topics
Building your own algorithm based on Kaggle data
Get to know how to implement and ML using python
Get insights from different datasets.
Requirements
Some programming background in python.
Description
This course is an intermediate course for professionals working in different industries that want to understand and get more insights from the data they manage at their work or from an aside project. The idea is to provide real hands on experience and an interactive approach to learn data science and some machine learning techniques. We will explore tools such as data visualization, statistics and machine learning as skills for analyzing data. The course include programming exercises with different datasets for python. We will be using additional tools such as Google Analytics to analyze and visualize data. Furthermore, we will discuss different application from different industries such as e-commerce, energy, medical and other business applications. Is intended for any kind of learner that already has some basic programming skills on python coding.The course will be divided into 2 main modules:1. Tools for data science.-ETL: Extract, Transform and Load.-Data visualization. -Statistical tools.2. Implementing data science.-Setting up a environment for data science.-Data visualization implementation.-Data science implementation.-Machine learning implementation.The main objectives of the course:1. Understand what are the main features and tools involved with data science.2. Understand and infer information from graphical sources.3. Show data insights through reports and other graphical tools.4. Implement statistical tools for analyzing the behavior and distribution of our data.5. Implement machine learning methods (specifically classification methods) to predict the behavior of our data.
Overview
Section 1: Introduction
Lecture 1 Welcome all!
Section 2: Data science tools
Lecture 2 ETL: Extract, Transform and Load Data
Lecture 3 Data visualization
Lecture 4 Statistics and Probability
Section 3: Data science implementation
Lecture 5 Setting up python environment for data science
Lecture 6 Data visualization on python and Google Analytics
Lecture 7 Data science implementation
Lecture 8 Machine learning implementation
Business persons that want to extend their knowledge on data visualization,Intermediate python developers that are willing to learn data science,Business persons that want to find another business opportunities
NitroFlare Link(s)
RapidGator Link(s)
Published 4/2023| Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 1.27 GB | Duration: 2h 35m
Machine learning, data visualization and hands on experience.
What you'll learn
Understand what are the main concepts behind data science for different industries
Learn about the tools available for data science
Getting real hands-on experience on the topics
Building your own algorithm based on Kaggle data
Get to know how to implement and ML using python
Get insights from different datasets.
Requirements
Some programming background in python.
Description
This course is an intermediate course for professionals working in different industries that want to understand and get more insights from the data they manage at their work or from an aside project. The idea is to provide real hands on experience and an interactive approach to learn data science and some machine learning techniques. We will explore tools such as data visualization, statistics and machine learning as skills for analyzing data. The course include programming exercises with different datasets for python. We will be using additional tools such as Google Analytics to analyze and visualize data. Furthermore, we will discuss different application from different industries such as e-commerce, energy, medical and other business applications. Is intended for any kind of learner that already has some basic programming skills on python coding.The course will be divided into 2 main modules:1. Tools for data science.-ETL: Extract, Transform and Load.-Data visualization. -Statistical tools.2. Implementing data science.-Setting up a environment for data science.-Data visualization implementation.-Data science implementation.-Machine learning implementation.The main objectives of the course:1. Understand what are the main features and tools involved with data science.2. Understand and infer information from graphical sources.3. Show data insights through reports and other graphical tools.4. Implement statistical tools for analyzing the behavior and distribution of our data.5. Implement machine learning methods (specifically classification methods) to predict the behavior of our data.
Overview
Section 1: Introduction
Lecture 1 Welcome all!
Section 2: Data science tools
Lecture 2 ETL: Extract, Transform and Load Data
Lecture 3 Data visualization
Lecture 4 Statistics and Probability
Section 3: Data science implementation
Lecture 5 Setting up python environment for data science
Lecture 6 Data visualization on python and Google Analytics
Lecture 7 Data science implementation
Lecture 8 Machine learning implementation
Business persons that want to extend their knowledge on data visualization,Intermediate python developers that are willing to learn data science,Business persons that want to find another business opportunities
NitroFlare Link(s)
Code:
RapidGator Link(s)
Code: