MP4 | Video: h264, 1280x720 | Audio: AAC, 48 KHz, 2 Ch

Genre: eLearning | Language: English + .srt | Duration: 78 lectures (7 hour, 59 mins) | Size: 1.92 GB

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.

Requirements

No Prior experience is required.

You'll need to install some software. We will show you how to do that step by step.

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.

Who this course is for:

Beginners to Data Science

Beginners to Machine Learning

Beginners to Python

Beginners to SQL