Advance Data Analyst: Data Analyst

During the Data Analyst: Data Analyst course, you’ll engage with knowledge and real-life case studies as you develop practical skills and techniques for immediate application to data analyst projects, or within your organization. You will be benefited from the unique pedagogy and multidisciplinary approach of Blackboard Learning—an institution at the forefront of research and online learning—as you develop data analyst skills to better understand Excel data analysis, Python for data science, and support vector machines and the factors that contribute to career success and failure.

Throughout this Data Analyst: Data Analyst course, developed by industry experts, you’ll get the opportunity to learn from experts with diverse experience. Guided by experts, Data Analyst: Data Analyst course prepares you to become a change-maker with the skills to drive your career or organization forward.

Data Analyst: Data Analyst course will demystify data analysts and give you the toolkit to make better contributions and to become an even greater asset to your organization. It will also allow you to communicate more effectively and confidently about data analyst issues, whether it is with the relevant people in your own business or with those outside your workplace.

After completing Data Analyst: Data Analyst course from Blackboard Learning, you will be more skillful with more knowledge, along with practical tips and advice that will help you to learn the essential aspects of data analysis. Skills development in data analysis leads you to career development in the data analyst sector.

Courses included in this Data Analyst: Data Analyst bundle course:

Enroll in the Data Analyst: Data Analyst course and get started with the Data Analyst: Data Analyst journey!

This Data Analyst: Data Analyst course is a course consisting of 5 courses with many data analyst-related topics.

You will get in this bundle course-

Course 1: SQL Queries 101

Course 2: Excel Model 101 - Google Drive

Course 3: Excel Data Analysis

Course 4: Learn Python for Data Science & Machine Learning from A-Z

Course 5: Learn Data Science and Machine Learning with R from A-Z

Certificate of completion

Digital certificate - Included

The Data Analyst: Data Analyst course contains important modules that teach learners about their professional needs and succession. In the United Kingdom, Blackboard Learning is one of the most popular online Data Analyst: Data Analyst course providers. You will get a solid foundation of knowledge about data analyst in this Data Analyst: Data Analyst course. You will be able to think critically about Data Analyst: Data Analyst and comprehend basic data analyst theories and methods. This Data Analyst: Data Analyst course was created to provide you with the tools and methods you'll need to make a measurable effect in your career, whether your objective is to land a job, improve your abilities, or make a good influence in some other way.

Curriculum for Data Analyst: Data Analyst bundle courses:

Course 1: SQL Queries 101

Unzipping the sample files.

• Creating the sample database.

• Basic Select Statements.

• Sorting the query with the order by statement.

• Using the where statement to filter the query.

• Creating subtotals using the group by statement.

• Introduction to using the join statement to create queries from more than 1 table.

Course 2: Excel Model 101 - Google Drive

Course 3: Excel Data Analysis

• Excel Data Analysis - Part 1

• Excel Data Analysis - Part 2

• Excel Data Analysis - Part 3

• Excel Data Analysis - Part 4

• Excel Data Analysis - Part 5

• Excel Data Analysis - Part 6

• Excel Data Analysis - Part 7

• Excel Data Analysis - Part 8

• Excel Data Analysis – Part 9

Course 4: Learn Python for Data Science & Machine Learning from A-Z

• Section 1: Introduction to Python for Data Science & Machine Learning from A-Z

• Who is this course for?

• Data Science + Machine Learning Marketplace

• Data Science Job Opportunities

• Data Science Job Roles

• What is a Data Scientist?

• How to Get a Data Science Job

• Data Science Projects Overview

• Section 2: Data Science & Machine Learning Concepts

• Why We Use Python

• What is Data Science?

• What is Machine Learning?

• Machine Learning Concepts & Algorithms

• What is Deep Learning?

• Machine Learning Vs Deep Learning

• Section 3: Python for Data Science

• What is Programming?

• Why Python for Data Science?

• What is Jupiter?

• What is Google Collab?

• Python Variables, Booleans

• Getting Started with Google Collab

• Python Operators

• Python Numbers & Booleans

• Python Strings

• Python Conditional Statements

• Python For Loops and While Loops

• Python Lists

• More about Lists

• Python Tuples

• Python Dictionaries

• Python Sets

• Compound Data Types & When to use each one?

• Python Functions

• Object-Oriented Programming in Python

• Section 4: Statistics for Data Science

• Intro To Statistics

• Descriptive Statistics

• Measure of Variability

• The measure of Variability Continued

• Measures of Variable Relationship

• Inferential Statistics

• Measure of Asymmetry

• Sampling Distribution

• Section 5: Probability and Hypothesis Testing

• What Exactly is Probability?

• Expected Values

• Relative Frequency

• Hypothesis Testing Overview

• Section 6: Numbly Data Analysis

• Intro Numbly Array Data Types

• Numbly Arrays

• Numbly Arrays Basics

• Numbly Array Indexing

• Numbly Array Computations

• Broadcasting

• Section 7: Pandas Data Analysis

• Intro To Pandas

• Intro To Pandas Continued

• Section 8: Python Data Visualization

• Data Visualization Overview

• Different Data Visualization Libraries in Python

• Python Data Visualization Implementation

• Section 9: Introduction to Machine Learning

• Intro to Machine Learning

• Section 10: Data Loading & Exploration

• Exploratory Data Analysis

• Section 11: Data Cleaning

• Feature Scaling

• Data Cleaning

• Section 12: Feature Selecting and Engineering

• Feature Engineering

• Section 13: Linear and Logistic Regression

• Linear Regression Intro

• Gradient Descent

• Linear Regression + Correlation Methods

• Linear Regression Implementation

• Logistic Regression

Course 5: Learn Data Science and Machine Learning with R from A-Z

• Section 1: Introduction to Data Science +ML with R from A-Z

• Intro To DS+ML Section Overview

• What is Data Science?

• Machine Learning Overview

• Who is this course for?

• Data Science + Machine Learning Marketplace

• DS+ ML Job Opportunities

• Data Science Job Roles

• Section 2: Getting Started with R

• Getting Started

• Basics

• Files

• R Studio

• Tidy verse

• Resources

• Section 3: Data Types and Structures in R

• Section Introduction

• Basic Types

• Vectors Part One

• Vectors Part Two

• Vectors: Missing Values

• Vectors: Coercion

• Vectors: Naming

• Vectors: Misc.

• Matrices

• Lists

• Introduction to Data Frames

• Creating Data Frames

• Data Frames: Helper Functions

• Data Frames: Tibbles

• Section 4: Intermediate R

• Section Introduction

• Relational Operators

• Logical Operators

• Conditional Statements

• Loops

• Functions

• Packages

• Factors

• Dates & Times

• Functional Programming

• Data Import/Export

• Databases

• Section 5: Data Manipulation in R

• Section Introduction

• Tidy Data

• The Pipe Operator

• Section 6: Data Visualization in R

• Section Introduction

• Getting Started

• Aesthetics Mappings

• Single Variable Plots

• Two-Variable Plots

• Facets, Layering, and Coordinate Systems

• Styling and Saving

• Section 7: Creating Reports with R Markdown

• Intro to R Markdown

• Section 8: Building Web Apps with R Shiny

• Intro to R Shiny

• A Basic Webapp

• Other Examples

• Section 9: Introduction to Machine Learning

• Intro to ML Part 1

• Intro to ML Part 2

• Section 10: Data Preprocessing

• Section Overview

• Data Preprocessing

Why Blackboard Learning:

Blackboard Learning is an online learning platform through which students from any corner of the world can learn their desired course. Using online learning, we assist students in realizing their full potential and advancing their careers. Today, our goal is to be the world's leading provider of online learning experiences with a global impact. By leveraging online learning, we assist students in preparing for bright futures in world-changing jobs. We provide a wide range of categories, including Accounting & IT, Programming, Creative, and more. Our courses are designed to stretch students intellectually through state-of-the-art online learning.

This Data Analyst: Data Analyst course is for anyone looking to develop their skills and knowledge in data analyst-related fields, as well as for those-

• Wants to enhance Data Analyst: Data Analyst-related skills and knowledge.
• Use data analyst-related knowledge in his career or profession.
• Needs data analyst-related skills for new job applications and opportunities.
• Who wants to learn Data Analyst: Data Analyst and apply it in real life?
• Anyone who wants to demonstrate Data Analyst: Data Analyst to prospective employers or jobs.
• Anyone who wants to apply for Data Analyst: Data Analyst course-related skills and dive into relevant career paths.

Data Analyst: Data Analyst course does not require prior knowledge or experience. Anyone with a PC, tablet, or mobile phone can do the Data Analyst: Data Analyst course. It would be ideal for the learner to have:

• An open mind, a spirit of self-inspection, and a willingness to improve himself/herself.
• A desire to improve business (and personal) knowledge and skills.
• The desire to enhance skills in data analysis.

This Data Analyst: Data Analyst course is exciting as it opens the doors to many professions related to data analysis. Prospective Data Analyst: Data Analyst course-related career paths that include but are not limited to-

• Data analyst
• Data insight professional
• Business analyst

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