Excel is enough, even if you don't know how to code!
This course enables non-majors to perform data analysis using Excel, covering everything from statistics to machine learning and Power Query.
The lecture content is really good. However, the volume is so different in each lecture that it is uncomfortable.
5.0
eunah-choi
100% enrolled
I really like it, starting from the very basics
5.0
neapps2022+inf
100% enrolled
This is a great lecture to easily understand the basic theories of data science.
What you will gain after the course
Data-driven decision making that brings practical results to business
Learning statistics to help understand data analysis
Quickly collect large-scale data through crawling and pivot tables
Unstructured data integration and management are possible with Power Query/Power Pivot.
Data visualization and insight identification with Power BI
You can do it with just Excel! Data analysis for math-phobes and beginners alike
🔬 Data analysis has become an essential skill!
Data, Artificial Intelligence, Machine Learning ... In this era of the 4th Industrial Revolution, what is the essential skill required regardless of the industry? It is data analysis capability.
-Looking at the pre-order results for the new product, a whopping 75% of people prefer red! Should we prepare the stock for the official launch with 75% red and 25% black?
-10% discount coupons led to a 3-fold increase in sales! If we increase the discount rate to 20%, what would the projected sales be?
-Which brands are hot lately and which ones are fading, and is there a way to see current trends at a glance?
Questions every office worker has had at least once, worries that are hard to find answers to the ability to read and analyze data, are no longer difficult if you have it.
Do you feel a gap between theory and practice? Are you unsure if it can actually be used in real work?
That's why we at IT Campus have prepared this. An all-encompassing course that can be applied immediately All in one Business Data AnalysisLecture<Data Science Introductory Bootcamp>
👍 Recommended for the following people
- Anyone who wants to build a career as a data scientist - Those who want to master everything from data concepts to business data analysis all at once - Those who want to learn statistical techniques based on data-analytical thinking, rather than just mathematics - Those who want to effectively evaluate business-related data, and perform actionable data analysis
Maso Campus's <Data Science Introductory Bootcamp> is a course designed so that even those who have given up on math, or lack confidence in it, can learn easily. Furthermore, to ensure anyone can utilize it easily, we conduct data analysis through ‘Excel’ rather than difficult programsor coding.
Therefore, anyone who wants to get started in data science will be able to easily analyze data!
👀 Course Features
Lectures that only list difficult concepts areNo!
Courses requiring prerequisites or prior knowledge are No!
It builds your capabilities so you can simply analyze real-world business problems on your own using Excel. Even for non-majors, we have distilled only the essentials so you can apply them directly to your work. Furthermore, because it is data analysis using the very familiar<Excel>, it is much easier to approach . And we provide a truly practical large-scale sales dataset that cannot be found anywhere else.
🏆 After completing the Data Science Introductory Bootcamp
Maso Campus's<Data Science Introductory Bootcamp>After taking this course, you only9 hours and 30 minutes will be able to apply data analysis directly to your work in just.
-Data preprocessing skills to collect & organize scattered data
-Data processing skills to effortlessly handle data used in real-world practice
-Data visualization skills to make even complex data easy to read
-Data-driven decision-making skills that lead to clear results
Data Science Introductory Bootcamp, you can take your perfect first step into data analysis using Excel, the most familiar tool in your daily work, .
📚 What you will learn
💬 Frequently Asked Questions Q&A
Q. Do I need any prior knowledge of Excel or data analysis? A. None at all. This course provides kind and detailed explanations so that even non-majors and complete Excel beginners can easily follow along. So don't worry and just give it a try. After completing the course, you will be able to 'properly' analyze data using Excel!
Q. I am a person who gave up on math and knows nothing about statistics. Will I have trouble taking the course? A. Not at all. To help you understand statistics and data analysis even without mathematical knowledge, I have prepared a core statistics lecture together with the course. Try challenging yourself to enter data science through Pearson and Bayesian statistics!
Q. Are there any requirements or prerequisites for taking this course? A. Since this is a practice-oriented course, it is recommended to have a dual monitor or an extra device to separate the lecture screen from the practice screen. Additionally, as the practice sessions are conducted based on Windows OS, we recommend taking the course in a Windows environment.
Q. I'm a complete beginner in data analysis and have never coded before, is it possible for me? A. Of course it is. This course does not use complex coding, but primarily utilizes the commonly used Excel to help you develop your data analysis skills.
✒️About the Instructor
✔ Please check before taking the course!
-Since this is a practice-oriented course, it is recommended to prepare a dual monitor or an extra device to separate the lecture screen and the practice screen. Additionally, as the practice is conducted based on Windows OS, we recommend taking the course in a Windows environment.
-The audio for this lecture was recorded at a somewhat low volume, so please check the [Preview] before taking the course.
-The lecture syllabus and practice files are located in the 00Textbook Download Centersection.
Recommended for these people
Who is this course right for?
Those who are new to data analysis
Office workers who need to produce meaningful results
Those who want to build a career as a data scientist
Those who want to learn business data analysis
Those who want to learn statistical techniques based on data-driven analytical thinking
Those who want to evaluate data effectively and conduct actionable data analysis
Need to know before starting?
As this is a practice-oriented course, we recommend using dual monitors or an extra device to separate the lecture screen from your practice screen.
Since the practice sessions are based on Windows OS, we recommend taking the course in a Windows environment.
No prior knowledge is required, as we will guide you step-by-step starting from the core statistics that form the foundation of data analysis.
"I will grow more than yesterday. And, I will help those who strive to grow more than yesterday."
With Actionable Content that embodies the sincerity and aspirations of Maso Campus,
100 million cumulative hours of lectures shared online and offline since 2013!
This precious experience and time are always the source of growth for both Maso Campus and our students.
The Miso Campus team strictly adheres to two principles for the growth of us all. 1. Actionable Content that can be put into practice immediately after learning. 2. Respecting the time and effort of participants.
The Miso Campus team strictly adheres to two principles for the growth of us all.
1. Actionable Content that you can actually use after learning
2. Time-Saving Curriculum that respects the participant's time and effort
Grow with Miso Campus's Actionable and Time-Saving Curriculum
1. Actionable Content that you can surely use once you learn it
2. Time-Saving Curriculum that respects the time and effort of participants
We hope you will walk the path of growth together with Masocampus's Actionable and Time-Saving Curriculum.
We hope you will walk the path of growth together with Maso Campus's Actionable and Time-Saving Curriculum.
Thank you for leaving a review! We will take into account the inconveniences you experienced while taking the course and use that information to create the course.