Data Analyst: Data Analyst Bundle Course

During the Data Analyst: Data Analyst (Data Analytics) course, you’ll engage with knowledge and real-life case studies as you develop practical skills and techniques for immediate application to data analysis projects, or within your organization. You will benefit from the unique pedagogy and multidisciplinary approach of Blackboard Learning—an institution at the forefront of research and online learning—as you develop data analysis skills to better understand the Excel formulas detailed, all about artforms, and hosting and website domain and the factors that contribute to career success and failure.

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

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

After completing the Data Analyst: Data Analyst (Data Analytics) 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 analysis sector.

Courses included in this Data Analyst: Data Analyst (Data Analytics) bundle course:

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

This Data Analyst: Data Analyst (Data Analytics) course is a course consisting of 12 courses with many data analysis-related topics.

You will get in this bundle course-

Course 1: Excel Data Analysis

Course 2: Building Robust Excel Models with Power Query, formulas, and VBA

Course 3: Compare two workbooks to find matches and variances with Excel VBA Tool

Course 4: Access Databases Volume2 - Forms and Reports

Course 5: ESP32 + Databases to Control Anything Anywhere

Course 6: Learn Python for Data Science & Machine Learning from A-Z

Course 7: Arduino Data Visualization using Python

Course 8: Arduino EEPROM Store Data Permanently on your Arduino

Course 9: Learn Data Science and Machine Learning with R from A-Z

Course 10: PLC Advance Course Data Registers and Internal Relays

Course 11: Clean Sensor Data with Filters

Course 12: Business Intelligence and Data Mining

The Data Analyst: Data Analyst (Data Analytics) 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 (Data Analytics) course providers. You will get a solid foundation of knowledge about data analysis in this Data Analyst: Data Analyst (Data Analytics) course. You will be able to think critically about Data Analyst: Data Analyst (Data Analytics) and comprehend basic data analysis theories and methods. This Data Analyst: Data Analyst (Data Analytics) 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 (Data Analytics) bundle courses:

Course 1: 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 2: Building Robust Excel Models with Power Query, formulas, and VBA

• Introduction.

• Prepaid expense models (resources).

• Accounting for prepaid expenses.

• Excel formulas detailed (Intro to three Excel models).

• Formula-based prepaid expenses model (schedule).

• Calculate prepaid expenses Amortization from the exact start date (payment date).

• Prepaid expenses summary with Power Query and Pivot Table.

• Advanced VBA prepaid expenses Amortization model.

• Bonus: Dynamic dashboard for divisional profit and loss statement(easy way).

• Thank you and super bonus.

Course 3: Compare two workbooks to find matches and variances with Excel VBA Tool

Course 4: Access Databases Volume2 - Forms and Reports

• Artforms

• Form Wizard

• Changing a form with a design view

• Adding controls to your form

Course 5: ESP32 + Databases to Control Anything Anywhere

• Introduction & Getting Started

• Introduction

• Who We Are

• Hardware And Software Requirements

• Important Note Review System

• Important Note Review System

• Getting Coding Environment Ready

• Download and install Arduino ESP and USB Driver

Course 6: 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 Colab

• 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

• 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

Course 7: Arduino Data Visualization using Python

• Introduction & Getting Started

• Introduction

• Who We Are?

• Hardware and Software Requirements

• Important Note: Review System

• Important Note: Review System

• Download and Install Software Section

Course 8: Arduino EEPROM Store Data Permanently on your Arduino

• Introduction & Getting Started

• Introduction
• Educational Engineering Team - Who are we?
• Hardware and Software Requirements
• Hardware and Software Requirements

Course 9: 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?

• 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

• {duly}: The Filter Verb

• {duly}: The Select Verb

• {duly}: The Mutate Verb

• {duly}: The Arrange Verb

• {duly}: The Summarize Verb

• Data Pivoting: {tidier}

• String Manipulation: {stringer}

• Web Scraping: {rest}

• JSON Parsing: {son lite}

Course 10: PLC Advance Course Data Registers and Internal Relays

• Introduction

• Introduction

• Who We Are

• Very Important Note Review Process

• Programmable Logic Controller

• Internal Relays and Data Registers

Course 11: Clean Sensor Data with Filters

• Introduction & Getting Started

• Introduction

• Who We Are

• Important Note Review System

• Important Note Review System

Course 12: Business Intelligence and Data Mining

• What is business intelligence?

• A strong case for understanding BI needs in different phases of business.

• The decision-making process and need for the IT system.

• Problem structure and decision support system.

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 (Data Analytics) course is for anyone looking to develop their skills and knowledge in data analysis-related fields, as well as for those-

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

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

• An open-minded, 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 (Data Analytics) course is exciting as it opens the doors to many professions related to data analysis. Prospective Data Analyst: Data Analyst (Data Analytics) course-related career paths that include but are not limited to

• Data analyst
• Data scientist
• Business analyst

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Certificate of completion

Digital certificate - Included