Data Science and Machine Learning For Beginners with Python

• 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.

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.