Published 2/2023MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 2.87 GB | Duration: 8h 54m

Gain skills you need to succeed as a data analyst.

What you'll learn

Connect to various data sources

Clean and transform data

Perform exploratory data analysis

Manipulate data using data frames

Create visualizations from data

Analyse data with SQL

Analyse data with Python

Analyse data with Power BI

Analyse data with R

Requirements

No prior coding experience required.

Description

Data analysis is a process of inspecting, cleansing, transfog, and modelling data with the goal of discovering useful information, infog conclusions, and supporting decision-making. A data analyst collects, organises and studies data to provide business insight.Data analyst applies various tools and techniques for data analysis and data visualisation (including the use of business information tools) to identify, collect and migrate data to and from a range of systems manage, clean, abstract and aggregate data alongside a range of analytical studies on that data manipulate and link different data sets summarise and present data and conclusions in the most appropriate format for users.R is a programming language. R is often used for statistical computing and graphical presentation to analyse and visualize data. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, -series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. SQL (Structured Query Language) is a programming language designed for managing data in a relational database. It's been around since the 1970s and is the most common method of accessing data in databases today. SQL has a variety of functions that allow its users to read, manipulate, and change data.Python is a popular programming language. Python can be used on a server to create web applications and also for data analysis and visualization. Analysing data with Python is an essential skill for Data Scientists and Data Analysts .Power BI is a cloud-based business analytics service from Microsoft that enables anyone to visualize and analyse data, with better speed and efficiency. It is a powerful as well as a flexible tool for connecting with and analysing a wide variety of data. Power BI also has a desktop version that can be used for data analysis and visualization.Gain skills you need to succeed as a data analyst! No prior coding experience required.

Overview

Section 1: Setting Up R Environment

Lecture 1 Introduction

Lecture 2 What is R

Lecture 3 Installing R on Windows

Lecture 4 Installing R on Macs

Lecture 5 What is R Studio

Lecture 6 Installing R Studio on Windows

Lecture 7 Installing R Studio on Macs

Lecture 8 Exploring R Studio Default Interface

Lecture 9 Creating a new project in R Studio

Lecture 10 What are Packages

Lecture 11 How to install Packages

Lecture 12 Data sets vs Data frames

Lecture 13 Loading Packages

Lecture 14 Importing data into R Studio

Lecture 15 How to read data in a csv file with R

Lecture 16 Installing Janitor Package

Lecture 17 Cleaning columns

Lecture 18 Selecting a subset of data

Lecture 19 Perfog multiple operations using Pipe operator

Lecture 20 Creating new columns from existing columns

Lecture 21 Create a new R Project

Lecture 22 Load data into new project

Lecture 23 What is Data Wrangling

Lecture 24 Data Wrangling steps

Lecture 25 Importance of data wrangling

Lecture 26 Perform Data Wrangling on Data

Lecture 27 Create a scatter plot

Lecture 28 Create a bar graph

Lecture 29 Adding Labels to plots

Section 2: SQL Server Environment Setup

Lecture 30 What is SQL Server

Lecture 31 What is SQL

Lecture 32 What is T-SQL

Lecture 33 SQL Server

Lecture 34 Install SQL Server

Lecture 35 SQL Server Editions

Lecture 36 Install SSMS

Lecture 37 Connect SSMS to SQL Server

Lecture 38 Sample Database

Lecture 39 Database Concepts

Lecture 40 Database Normalisation

Lecture 41 Create database

Section 3: Data Exploration with SQL

Lecture 42 Data Preparation

Lecture 43 Importing Datasets into database

Lecture 44 How many continents do we have data for

Lecture 45 What is possibility of dying from COVID

Lecture 46 What percentage of population is infected with COVID

Lecture 47 What countries has highest COVID infection per population

Lecture 48 What countries has the highest deaths from COVID

Lecture 49 What continent has highest deaths from COVID

Lecture 50 What are the global COVID cases and death

Lecture 51 What number of people have been vaccinated against COVID

Lecture 52 Analysing data with SQL CTE

Lecture 53 Using temporary tables for data

Lecture 54 Using Views for data

Section 4: Python Environment Setup

Lecture 55 What is Python

Lecture 56 What is Jupyter Notebook

Lecture 57 Installing Jupyter Notebook Server

Lecture 58 Running Jupyter Notebook Server

Lecture 59 Common Jupyter Notebook Commands

Lecture 60 Jupyter Notebook Components

Lecture 61 Jupyter Notebook Dashboard

Lecture 62 Jupyter Notebook Interface

Lecture 63 Creating a new Jupyter Notebook

Section 5: Data Analysis and visualization with Python

Lecture 64 Kaggle Datasets

Lecture 65 Tabular data

Lecture 66 Exploring Pandas DataFrame

Lecture 67 Analysing and manipulating pandas dataframe

Lecture 68 What is data cleaning

Lecture 69 Basic data cleaning

Lecture 70 Data Visualization

Lecture 71 Visualizing qualitative data

Lecture 72 Visualizing quantitative data

Section 6: Data Analysis & Visualization with Power BI

Lecture 73 Microsoft 365

Lecture 74 Getting started with Microsoft 365

Lecture 75 What is Power BI

Lecture 76 What is Power BI Desktop

Lecture 77 Installing Power BI Desktop

Lecture 78 Exploring Power BI Desktop

Lecture 79 Power BI Overview - Part 1

Lecture 80 Power BI Overview - Part 2

Lecture 81 Power BI Overview - Part 3

Lecture 82 Components of Power BI

Lecture 83 Building blocks of Power BI

Lecture 84 Power BI Service

Lecture 85 Connecting to web data

Lecture 86 Clean and transform data - Part 1

Lecture 87 Clean and transform data - Part 2

Lecture 88 Combining data sources

Lecture 89 Data visualization with Power BI - Part 1

Lecture 90 Data visualization with Power BI - Part 2

Lecture 91 Publishing reports to Power BI Service

Lecture 92 Connect Power BI to SQL Server

Lecture 93 Import SQL Data into Power BI

Lecture 94 Analyze data & create visualization

Lecture 95 How to Publish your report to Power BI Service

Bner Data Analyst,Bner Data Scientist

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