This course is designed with hyper-efficient methods so that you can learn all basic communication skills basics in less than 45 minutes.

What will students achieve or be able to do after taking this course?

Communicate effectively to individuals and small groups
Deliver presentations
Display basic public speaking skills
Communicate messages in an understandable and memorable way
Demonstrate mastery of all basic communication skills

Whether you're working for a company or running your own, being able to make better decisions requires you to be able to analyze and interpret data.

What data do you need? How do you prep that data? How do you analyze it to answer specific questions?

In this course, we're going to show you step-by-step, exactly how to do that, by starting with the very basics.

This course is as much about Excel, if not more, than data analysis concepts and techniques. Excel is still the most popular tool used by analysts in all industries, across all roles. It's used by financial analysts, marketing analysts, sales analysts, and of course, data analysts.

In this course, you will learn how to;
- calculate mean, median, mode, minimum, maximum, quartiles, variance, and standard deviation from some numbers.
- analyze a population using data samples.
- group data
- formulate hypothesis, interpret your analysis, and get an idea of the limitations of building hypothesis.

This course covers the acquisition of data literacy, mastering of data language, familiarization with modern business analytics techniques. The learner will learn how to interprete data professionally, use data to improve business decisions, make better and faster decisions using data. and uncover findings and insights independently.

The course provides the complete preparation you need to become a data analyst. Learn how to obtain interesting, real-time information from an API with a simple script. Complete a data cleaning exercise on absenteeism rate. Go through a complete loan data case study and apply your NumPy skills. Learn how to create pie, bar, line, area, histogram, scatter, regression, and combo charts.

You will understand different data types and their memory usage, how to clean data with pandas Series and DataFrames, expand your knowledge of NumPy-statistics and preprocessing and engage with coding exercises that will prepare you for the job.

A comprehensive, in-detail course for beginners to advanced Data Scientists. In this course, you will learn storytelling with data, data visualization, how to create rich informative data graphs, speak the language of data, and discover important contexts to understand data.

You can turn default graphs from tools such as Excel and Google Sheets into effective data communications, craft compelling narratives with data, create impactful data visualizations, and format your graphs for impact.

Data exploration is the initial step in data analysis, where users explore a large data set in an unstructured way to uncover initial patterns, characteristics, and points of interest. This process isn�t meant to reveal every bit of information a dataset holds, but rather to help create a broad picture of important trends and major points to study in greater detail. Data exploration can use a combination of manual methods and automated tools such as data visualizations, charts, and initial reports.

Exploratory Data Analysis (EDA) is the first step in your data analysis process. Here, you make sense of the data you have and then figure out what questions you want to ask and how to frame them, as well as how best to manipulate your available data sources to get the answers you need. You do this by taking a broad look at patterns, trends, outliers, unexpected results and so on in your existing data, using visual and quantitative methods to get a sense of the story this tells. You�re looking for clues that suggest your logical next steps, questions or areas of research.

This course prepares participants to begin running data analysis on databases. Both univariate and multivariate analysis are covered with a particular focus on regression analysis. Regression analysis is done in Excel, SAS, and Stata to give viewers a sense of familiarity with a variety of different software package structures. The focus in this course is on financial data though the techniques are also applicable to more general forms of data like that used in marketing or management analyses.

If you would like Continuing Education Credit (e.g. CPE, CE, CPD, etc.) for this course, it is available if you take this course on the Illumeo dot com platform under course title: Business Intelligence - Fundamentals of Data Analysis. Illumeo is certified to provide CPE in over two dozen different professional certifications covering finance, accounting, treasury, internal audit, HR, and more. However, in order to receive CPE credit the courses must be taken on an �approved-by-the-governing-body� CPE platform, and for over two dozen corporate professional certifications, that is the Illumeo platform. Go to Illumeo dot com to learn more.

In this course we use a real data-set to practice what is taught in each of the lecture videos. By the end of this course you will be able to explain why some females earn less than males and be able to identify (and measure) where gender wage discrimination is taking place and where not.

The techniques taught in this course are all executable in Microsoft Excel and will help you improve your current analysis skills. The topics cover:

- Using averages and means
- Using counts and medians
- Data visualizations (graphs and plots)
- Correlations and scatter-plots
- Histograms to describe the shape of data
- How to easily understand and use variance and standard deviation
- How to construct and use "confidence intervals"
- Hypothesis testing
- Using t-tests to prove or disprove an assumption

This course now includes free access to our Data Fundamentals Handbook, which compliments all the video content in this course in written form.

This course starts with an introduction to the world of data. Context is critical, and it most definitely applies to learning how to work with data. Before even touching a data tool, amongst many other things, we believe it's vital that one fully understands the context surrounding data.

From there you'll delve deep in to the differences between Data Analytics, Data Science, and Data Engineering, and how each of these roles provide value in their own way. In addition, you'll gather a deep understanding of the tools used by professionals � which are the most popular, when one would be preferred over another, and how they can be used in collaboration.

Next, you'll learn about the technical processes that encompass the lineage of data. This section will enable you to internalize the concept of a Data Pipeline, and start building-up a lexicon and literacy for how data moves from collection to analysis.

Finally, you'll see a step-by-step learning roadmap to become a practitioner of Data Analytics. In this section you'll gain access to recommended steps to take after this course, and career paths that are most relevant.

In this course, we will teach you the comprehensive data analysis skills to derive insights from data.

We will illustrate the following broad content topics in great detail in this course:

1) Data mining using slicers, pivot-tables and pivot-graphs in Excel

2) Data analysis in Excel

3) Deriving actionable insights from data analysis

4) Undertake management level discussion on key insights from data analysis

It is a very comprehensive course that will teach you the complete skills to do advanced data analysis in Excel.

Tableau Certification is becoming more prevalent these days and I'm not surprised. The demand for Data Skilled workers has been rising exponentially in the last couple of decades, and believe it or not, there's a shortage. Companies are recruiting heavily and upskilling those they can. The only course on Udemy that teaches the complete Tableau Platform; Desktop, Online, Prep, Bridge and Conductor!

Most instructors only teach Tableau Desktop which is the visualization tool. I'll teach you the entire ecosystem from data cleansing and preparation, to data ETL, automation, Story Telling, Tableau Online and Server and much more.

This course is designed specifically for those who do not have a data background or experience and want to be more efficient in the way they clean, prepare and share data.

It has also been designed specifically to pass the Tableau Certifications by preparing you for the Tableau Desktop Specialist Practice Exam as well as the others depending on how far you want to go. We'll be doing assignments and lessons throughout which mirror some of the Tableau Desktop Specialist Exam Questions.

Tableau Advanced Training: Master Tableau in Data Science
Master Tableau in Data Science by solving Real-Life Analytics Problems. Learn Visualisation and Data Mining by doing!
Ready to take your Tableau skills to the next level?
Want to truly impress your boss and the team at work?
In this course you will learn:
- How to use Groups and Sets to increase your work efficiency 10x
- How to use Dynamic Sets
- How to Control Sets With Parameters
- Everything about Table Calculations and how to use their power in your analysis
- How to perform Analytics and Data Mining in Tableau
- How to create Animations in Tableau
- And much, much more!

This course covers the content required for the PL-300 certification exam. It has been updated in line with the March-June 2023 User Interface update for Power BI Desktop on-object interaction, the updated Power BI Service User Interface, and the PL-300 exam updates as of 6 February and 23 April 2024.

Do you already use reporting software such as Access, SSRS, Tableau or WebI? Or is this your first reporting software tool? Either way, welcome.

In this course, learn the skills that Microsoft want you to know, and add another tool to your CV, and even go for the Microsoft Power BI certification.

Power BI is one of the most requested reporting tools that are requested in the job market, and the ability to being able to use it now could be very useful for your current work, and your next job hunt.

In business, being able to understand, harness, and use data is no longer a skill reserved for a handful of well-paid analysts. It's becoming an essential part of many roles.

If that sounds daunting, don't worry. There is a growing set of tools designed to make data analysis accessible to everyone, in this huge-value, four-course Data Analysts Toolbox bundle we look in detail at three of those tools: Excel, Python, and Power BI.

In isolation Excel, Python, and Power BI are useful and powerful. Learn all three and you are well on your way to gaining a much deeper understanding of how to perform complex data analysis.

This Data Analysts Toolbox bundle is aimed at intermediate Excel users who are new to Python and Power BI. All courses include practice exercises so you can put into practice exactly what you learn.

In this course we are going to show you how to supercharge your Google Sheets into Interactive Dashboards and incredible reports. Data Studio works seamlessly with your Google Sheets data to create amazing data analysis in minutes.

Data Studio is an incredibly easy to use drag and drop tool that allows a multitude of different visualizations to be created in minutes. The addition of filtering tools produces stunning reports that will take your data analysis to the next level.

Data Studio is available free to people with a Google or Gmail account.

Ready to start a career in Data Analysis but don�t know where to begin? This course presents you with a gentle introduction to Data Analysis, the role of a Data Analyst, and the tools used in this job. You will learn about the skills and responsibilities of a data analyst and hear from several data experts sharing their tips & advice to start a career. This course will help you to differentiate between the roles of Data Analysts, Data Scientists, and Data Engineers.

You will familiarize yourself with the data ecosystem, alongside Databases, Data Warehouses, Data Marts, Data Lakes and Data Pipelines. Continue this exciting journey and discover Big Data platforms such as Hadoop, Hive, and Spark.

By the end of this course you�ll be able to understand the fundamentals of the data analysis process including gathering, cleaning, analyzing and sharing data and communicating your insights with the use of visualizations and dashboard tools.

In this project, you will learn the foundation of data analysis with Microsoft Excel using sales data from a sample company. You will learn how to use sorting and filtering tools to reorganize your data and access specific information about your data. You will also learn about the use of functions like IF and VLOOKUP functions to create new data and relate data from different tables.

Finally, you will learn how to create PivotTables to summarize and look at comparisons within your data. These skills will help you efficiently perform data analysis on many different types of data and give you the foundation to expand your toolbox as you explore other strategies for data analysis.

By the end of this course, learners are provided a high-level overview of data analysis and visualization tools, and are prepared to discuss best practices and develop an ensuing action plan that addresses key discoveries. It begins with common hurdles that obstruct adoption of a data-driven culture before introducing data analysis tools (R software, Minitab, MATLAB, and Python). Deeper examination is spent on statistical process control (SPC), which is a method for studying variation over time. The course also addresses do�s and don�ts of presenting data visually, visualization software (Tableau, Excel, Power BI), and creating a data story.

Material features online lectures, videos, demos, project work, readings and discussions. This course is ideal for individuals keen on developing a data-driven mindset that derives powerful insights useful for improving a company�s bottom line. It is helpful if learners have some familiarity with reading reports, gathering and using data, and interpreting visualizations.

The Data Analysis and Interpretation Specialization takes you from data novice to data expert in just four project-based courses. You will apply basic data science tools, including data management and visualization, modeling, and machine learning using your choice of either SAS or Python, including pandas and Scikit-learn. Throughout the Specialization, you will analyze a research question of your choice and summarize your insights. In the Capstone Project, you will use real data to address an important issue in society, and report your findings in a professional-quality report. You will have the opportunity to work with our industry partners, DRIVENDATA and The Connection. Help DRIVENDATA solve some of the world's biggest social challenges by joining one of their competitions, or help The Connection better understand recidivism risk for people on parole in substance use treatment. Regular feedback from peers will provide you a chance to reshape your question. This Specialization is designed to help you whether you are considering a career in data, work in a context where supervisors are looking to you for data insights, or you just have some burning questions you want to explore. No prior experience is required. By the end you will have mastered statistical methods to conduct original research to inform complex decisions.

This course welcomes everyone with a desire to unlock the power of data storytelling! Whether you're a business professional navigating the world of data analysis, a student embarking on your data journey, or a marketer looking to make your presentations soar, this beginner-friendly course lays the foundation for effective data communication.

Technical expertise? Not required! While the course doesn't teach specific visualization tools like Tableau or Power BI, it rather shares knowledge about storytelling principles that breathe life into visualizations and analyses. For those already well-versed in technical skills, this course acts as a bridge, transforming your data and charts into a captivating narrative that resonates with any audience.

For non-technical learners, this journey equips you to contribute confidently to data-driven projects and understand what goes behind impactful presentations. You'll discover how to frame your data as a compelling story, ensuring your voice is heard clearly and your insights take center stage.

Welcome to the Data Storytelling with Power BI course, where you'll embark on a journey to acquire practical expertise in data transformation and visualization. Leverage the potential of Power BI to craft narratives through structured data, leading to the discovery of more profound insights. Throughout this course, you'll explore the industry-specific applications of Power BI and delve into its various features and functionalities.

This course is designed for a diverse audience: freshers, data analyst, business analysts, business intelligence analyst and IT professionals who are looking to enhance their data analysis skills through Power BI.

Prior experience with Microsoft Excel or spreadsheet applications can be beneficial when working with Power BI.

This Specialization provides an introduction to data literacy knowledge and helps learners build practical skills to explore and visualize data. Using real-world applications, the Specialization starts by building a foundational understanding of data and teaches learners to prepare, explore, analyze, visualize, and communicate data. New to analyzing data? This Specialization is for you, focusing on practical understanding while avoiding complicated statistical terminology.

Applied Learning Project

Through the SAS Data Literacy: Exploring and Visualizing Data Specialization, you get access to hands-on projects that are built into the course work. Examples of projects include Visual Analytics Methodology, Preparing Data Using SAS Data Studio, Analyzing Data with SAS Visual Analytics, and Designing Reports with SAS Visual Analytics.

This course introduces you to how to use spreadsheets and SQL queries to analyze and extract data. You will learn how to practically apply the OSEMN data analysis framework and spreadsheet functions to clean data, calculate summary statistics, evaluate correlations, and more. You�ll also dive into common data visualization techniques and learn how to use dashboards to tell a story with your data.

By the end of this course you will be able to:
� Clean data with spreadsheets
� Use common spreadsheet formulas to calculate summary statistics
� Identify data trends and patterns
� Write foundational SQL statements and queries to extract data in spreadsheets
� Create charts in Google Sheets and use Tableau to visualize data
� Use dashboards to create data visualizations

This is a self-paced lab that takes place in the Google Cloud console. This lab demonstrates how to use Google Data Studio to visualize data stored in Google Cloud SQL.

What you will learn:
- Create BigQuery views
- Create a BigQuery Datasource in Google Data Studio
- Create a Data Studio report with a date range control
- Create multiple charts using BigQuery views