• Post category:StudyBullet-3
  • Reading time:28 mins read


Learn to Analyse , Make Predictions, Explore data Frames,Clean and Visualize Data

What you will learn

Install Jupyter Notebook Server

Create a new notebook

Explore Components of Jupyter Notebook

Understand Data Science Life Cycle

Use Kaggle Data Sets

Perform Probability Sampling

Explore and use Tabular Data

Explore Pandas DataFrame

Manipulate Pandas DataFrame

Perform Data Cleaning

Perform Data Visualization

Visualize Qualitative Data

Explore Machine Learning Frameworks

Understand Supervised Machine Learning

Use machine learning to predict value of a house

Use Scikit-Learn

Load datasets

Make Predictions using machine learning

Understand Python Expressions and Statements

Understand Python Data Types and how to cast data types

Understand Python Variables and Data Structures

Understand Python Conditional Flow and Functions

Learn SQL with PostgreSQL

Perform SQL CRUD Operations on PostgreSQL Database

Filter and Sort Data using SQL

Understand Big Data Terminologies.

Install Jupyter Notebook Server

Create a new notebook

Explore Components of Jupyter Notebook

Understand Data Science Life Cycle

Use Kaggle Data Sets

Perform Probability Sampling


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Explore and use Tabular Data

Explore Pandas DataFrame

Manipulate Pandas DataFrame

Perform Data Cleaning

Perform Data Visualization

Visualize Qualitative Data

Explore Machine Learning Frameworks

Understand Supervised Machine Learning

Use machine learning to predict value of a house

Use Scikit-Learn

Load datasets

Make Predictions using machine learning

Understand Python Expressions and Statements

Understand Python Data Types and how to cast data types

Understand Python Variables and Data Structures

Understand Python Conditional Flow and Functions

Learn SQL with PostgreSQL

Perform SQL CRUD Operations on PostgreSQL Database

Filter and Sort Data using SQL

Understand Big Data Terminologies.

Description

Data science is the study of data. It involves developing methods of recording, storing, and analyzing data to effectively extract useful information . Data is a fundamental part of our everyday work, whether it be in the form of valuable insights about our customers, or information to guide product,policy or systems development.   Big business, social media, finance and the public sector all rely on data scientists to analyse their data and draw out business-boosting insights.

Python is a dynamic modern object -oriented programming language that is easy to learn and can be used to do a lot of things both big and small. Python is what is referred to as a high level language. That means it is a language that is closer to humans than computer.It is also known as a general purpose programming language due to it’s flexibility. Python is used a lot in data science. 

Machine learning relates to many different ideas, programming languages, frameworks. Machine learning is difficult to define in just a sentence or two. But essentially, machine learning is giving a computer the ability to write its own rules or algorithms and learn about new things, on its own. In this course, we’ll explore some basic machine learning concepts and load data to make predictions.

We will also be using SQL to interact with data inside a PostgreSQL Database.

What you’ll learn

  • Understand Data Science Life Cycle
  • Use Kaggle Data Sets
  • Perform Probability Sampling
  • Explore and use Tabular Data
  • Explore Pandas DataFrame
  • Manipulate Pandas DataFrame
  • Perform Data Cleaning
  • Perform Data Visualization
  • Visualize Qualitative Data
  • Explore Machine Learning Frameworks
  • Understand Supervised Machine Learning
  • Use machine learning to predict value of a house
  • Use Scikit-Learn
  • Load datasets
  • Make Predictions using machine learning
  • Understand Python Expressions and Statements
  • Understand Python Data Types and how to cast data types
  • Understand Python Variables and Data Structures
  • Understand Python Conditional Flow and Functions
  • Learn SQL with PostgreSQL
  • Perform SQL CRUD Operations on PostgreSQL Database
  • Filter and Sort Data using SQL
  • Understand Big Data Terminologies

A Data Scientist can work as the following:

  • data analyst.
  • machine learning engineer.
  • business analyst.
  • data engineer.
  • IT system analyst.
  • data analytics consultant.
  • digital marketing manager.

Data science is the study of data. It involves developing methods of recording, storing, and analyzing data to effectively extract useful information . Data is a fundamental part of our everyday work, whether it be in the form of valuable insights about our customers, or information to guide product,policy or systems development.   Big business, social media, finance and the public sector all rely on data scientists to analyse their data and draw out business-boosting insights.

Python is a dynamic modern object -oriented programming language that is easy to learn and can be used to do a lot of things both big and small. Python is what is referred to as a high level language. That means it is a language that is closer to humans than computer.It is also known as a general purpose programming language due to it’s flexibility. Python is used a lot in data science. 

Machine learning relates to many different ideas, programming languages, frameworks. Machine learning is difficult to define in just a sentence or two. But essentially, machine learning is giving a computer the ability to write its own rules or algorithms and learn about new things, on its own. In this course, we’ll explore some basic machine learning concepts and load data to make predictions.

We will also be using SQL to interact with data inside a PostgreSQL Database.

What you’ll learn

  • Understand Data Science Life Cycle
  • Use Kaggle Data Sets
  • Perform Probability Sampling
  • Explore and use Tabular Data
  • Explore Pandas DataFrame
  • Manipulate Pandas DataFrame
  • Perform Data Cleaning
  • Perform Data Visualization
  • Visualize Qualitative Data
  • Explore Machine Learning Frameworks
  • Understand Supervised Machine Learning
  • Use machine learning to predict value of a house
  • Use Scikit-Learn
  • Load datasets
  • Make Predictions using machine learning
  • Understand Python Expressions and Statements
  • Understand Python Data Types and how to cast data types
  • Understand Python Variables and Data Structures
  • Understand Python Conditional Flow and Functions
  • Learn SQL with PostgreSQL
  • Perform SQL CRUD Operations on PostgreSQL Database
  • Filter and Sort Data using SQL
  • Understand Big Data Terminologies

A Data Scientist can work as the following:

  • data analyst.
  • machine learning engineer.
  • business analyst.
  • data engineer.
  • IT system analyst.
  • data analytics consultant.
  • digital marketing manager.
English
language
Content
Introduction and Setup
Introduction
What is Jupyter Notebook
Installing Jupyter Notebook Server
Running Jupyter Notebook Server
Common Jupyter Notebook Commands
Jupyter Notebook Components
Jupyter Notebook Dashboard
Jupyter Notebook User Interface
Creating a new Notebook
Python Fundamentals
What is Python
Python Expressions
Python Statements
Python Comments
Python Data Types
Casting Data Type
Python Variables
Python List
Python Tuple
Python Dictionaries
Python Operators
Python Conditional Statements
Python Loops
Python Functions
Data Science
What is Data Science
Impact of Data Science
Data Science life cycle
Data Science Terminologies
Kaggle Data Sets
Probability Sampling
Tabular Data
Exploring Pandas DataFrame
Manipulating a Pandas DataFrame
What is Data Cleaning
Basic Data Cleaning Process
What is Data Visualization
Visualizing Qualitative Data : Part 1
Visualizing Qualitative Data : Part 2
Introduction to Machine Learning with Python
Installing Python
Installing Pycharm on Windows
Installing Pycharm on Macs
Installing Anaconda
What is Machine Learning
Machine Learning Frameworks
Machine Learning Vocabulary
Supervised machine learning
Where Machine Learning is used
Creating a basic house value estimator
Using Scikit-Learn
Loading a dataset part 1
Loading a dataset part 2
Making Predictions part 1
Making Predictions part 2
SQL and Data Science with PostgreSQL
What is SQL
What is PostgreSQL
Installing PostgreSQL on windows
Installing PostgreSQL on Mac
Connecting to a PostgreSQL Database
Database Concepts
Install Sample Database
What is CRUD
Data Types
SQL CREATE TABLE Statement
SQL INSERT Statement
SQL SELECT Statement
SQL UPDATE Statement
SQL WHERE clause
SQL ORDER BY Clause
Introduction to Big Data Terminology
What is Big Data
What is high volume
What is high variety
What is high velocity
Google’s Big Data Approach
What is a cluster
What is a Node
Google File System
Google’s Big Table
What is MapReduce
Apache Hadoop
Introduction and Setup
Introduction
What is Jupyter Notebook
Installing Jupyter Notebook Server
Running Jupyter Notebook Server
Common Jupyter Notebook Commands
Jupyter Notebook Components
Jupyter Notebook Dashboard
Jupyter Notebook User Interface
Creating a new Notebook
Python Fundamentals
What is Python
Python Expressions
Python Statements
Python Comments
Python Data Types
Casting Data Type
Python Variables
Python List
Python Tuple
Python Dictionaries
Python Operators
Python Conditional Statements
Python Loops
Python Functions
Data Science
What is Data Science
Impact of Data Science
Data Science life cycle
Data Science Terminologies
Kaggle Data Sets
Probability Sampling
Tabular Data
Exploring Pandas DataFrame
Manipulating a Pandas DataFrame
What is Data Cleaning
Basic Data Cleaning Process
What is Data Visualization
Visualizing Qualitative Data : Part 1
Visualizing Qualitative Data : Part 2
Introduction to Machine Learning with Python
Installing Python
Installing Pycharm on Windows
Installing Pycharm on Macs
Installing Anaconda
What is Machine Learning
Machine Learning Frameworks
Machine Learning Vocabulary
Supervised machine learning
Where Machine Learning is used
Creating a basic house value estimator
Using Scikit-Learn
Loading a dataset part 1
Loading a dataset part 2
Making Predictions part 1
Making Predictions part 2
SQL and Data Science with PostgreSQL
What is SQL
What is PostgreSQL
Installing PostgreSQL on windows
Installing PostgreSQL on Mac
Connecting to a PostgreSQL Database
Database Concepts
Install Sample Database
What is CRUD
Data Types
SQL CREATE TABLE Statement
SQL INSERT Statement
SQL SELECT Statement
SQL UPDATE Statement
SQL WHERE clause
SQL ORDER BY Clause
Introduction to Big Data Terminology
What is Big Data
What is high volume
What is high variety
What is high velocity
Google’s Big Data Approach
What is a cluster
What is a Node
Google File System
Google’s Big Table
What is MapReduce
Apache Hadoop