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

What you’ll 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.

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.

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