The Ultimate Data Science (Python & R) Course: All In One

Learn to use data science and statistics to solve business problems and gain insights into everyday problems.

What you'll learn
Introduction to Data Science
Learn and Understand the Key Data Science Concepts
Understanding Python Pandas
Learn and Understand Bokeh
Learn How to Manage Packages
Understanding Machine Learning with Scikit-Learn
Learn How to Analyze your data efficiently with the most powerful data science stack
Learn How to Perform cleaning, sorting, classification, clustering, regression, and dataset modeling using Anaconda
Requirements
Basic Python programming knowledge is helpful but not required
Description
Welcome to this course. You might already know that there’s a wealth of data science and machine learning resources available on the market, but what you might not know is how much is left out by most of these AI resources. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining. This course not only covers everything you need to know about algorithm families but also ensures that you become an expert in everything, from the critical aspects of avoiding bias in data to model interpretability, which have now become must-have skills. Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. This course gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. If you’re a data analyst or data science professional looking to make the most of Anaconda’s capabilities and deepen your understanding of data science workflows, then this course is for you. You don’t need any prior experience with Anaconda, but a working knowledge of Python and data science basics is a must.This course seeks to fill all those gaps and has a comprehensive syllabus that tackles all the major components of data science knowledge. You will be using data science to solve common business problems throughout this course. You will start with the basics of Python, Pandas, Scikit-learn, NumPy, Keras, Prophet, statsmod, SciPy, and more. You will learn statistics and probability for data science in detail. Then, you will learn visualization theory for data science and analytics using Seaborn, Matplotlib, and Plotly.In this course, you'll learn:Introduction to Data ScienceLearn and Understand the Key Data Science ConceptsUnderstanding Python PandasLearn and Understand Bokeh Learn How to Manage PackagesUnderstanding Machine Learning with Scikit-LearnLearn How to Analyze your data efficiently with the most powerful data science stackLearn How to Perform cleaning, sorting, classification, clustering, regression, and dataset modeling using AnacondaAt the end of the course, you will learn all the major components of data science and gain the confidence to enter the world of data science.

Overview

Section 1: Welcome

Lecture 1 Introduction

Section 2: Getting Started

Lecture 2 Learning Jupyter Basics

Lecture 3 Learning Python Pandas - Learn How to Analyze Data

Lecture 4 Learning Bokeh Basics - Learn How to Visualize Data

Lecture 5 Machine Learning with Scikit-Learn

Section 3: Data Science - Understanding the Key Concepts

Lecture 6 Introduction

Lecture 7 Empowering the Data Science team

Lecture 8 Understanding Data Science Development Workflow

Section 4: Data Science - Learning Python Pandas

Lecture 9 Learn About Pandas DataFrames

Lecture 10 Python Pandas - Creating Columns & Modifying Data

Lecture 11 Understanding Data Selection - Boolean Masks

Lecture 12 Learn How to Read Data - Part 1

Lecture 13 Learn How to Read Data - Part 2

Lecture 14 Learn How to Group Data Together

Lecture 15 Learn How to Connect to a Database - Part 1

Lecture 16 Learn How to Connect to a Database - Part 2

Lecture 17 Learn About Time Series Data

Lecture 18 Using Pandas to Read and Write Files

Lecture 19 Section Summary

Section 5: Data Science - Introduction to Anaconda Platform

Lecture 20 Python & R Open Source Analytics

Lecture 21 Learn and Understand Conda

Lecture 22 Learn About Anaconda Components

Lecture 23 Parallel Data Processing

Lecture 24 Learning Data Science Workflows

Lecture 25 Creating a New Project

Web Developers,Software Developers,Programmers,Anyone interested in Data Science