Data Literacy: Statistical Thinking and Data Analysis Fundamentals for the AI Era

In the era of AI and Big Data, are you utilizing your organization's data effectively? This course builds essential capabilities for reading and interpreting data, covering everything from the foundations of statistical thinking to the core principles of machine learning and deep learning. Grow into a practical leader capable of discovering patterns amidst volatility and making data-driven decisions.

1 learners are taking this course

Level Beginner

Course period 1 months

data-analysis
data-analysis
AI
AI
classifier
classifier
Data literacy
Data literacy
Probability and Statistics
Probability and Statistics
data-analysis
data-analysis
AI
AI
classifier
classifier
Data literacy
Data literacy
Probability and Statistics
Probability and Statistics

What you will gain after the course

  • Ability to provide appropriate opinions on practical statistics and analysis results

  • Understanding the basic principles of machine learning, text analysis, and deep learning

  • Establishing a statistical thinking framework for data-driven decision making

Does data feel vague and overwhelming?
In the AI era, use it as a core competency!
Bạn cảm thấy dữ liệu thật mơ hồ?
Hãy sử dụng nó như một năng lực cốt lõi trong kỷ nguyên AI!

Data literacy goes beyond simply looking at numbers; it is the ability to discover hidden patterns through data and make decisions based on logical thinking. This course presents practical methods to turn data into your own weapon, covering everything from the basics of statistical thinking to the principles of machine learning and deep learning.


Have you ever felt overwhelmed and unsure of where to start when instructed to analyze your company's vast amount of data?

Have you felt frustrated because you weren't sure how to practically apply new AI technology to your business ahead of its introduction?

Have you ever had a moment where you received data analysis results but hesitated to make an important decision because you couldn't properly interpret the meaning within them?

Make data an opportunity for growth rather than an object of fear. Through this course, you will be reborn as an expert in data-driven
decision-making.

Explore everything from the essence of data to statistical thinking
and the core principles of machine learning.


Develop the ability to interpret data accurately and
grow into a data expert leading the AI era..

✔️

Data Literacy: Statistical Thinking and Data Analysis Fundamentals in the AI Era
Strengthening Essential Data Analysis Competencies for the AI Age

In the era of AI and big data, utilizing data effectively is a necessity, not an option. This course systematically builds all the competencies required to read and interpret data, from the basics of statistical thinking to the core principles of machine learning and deep learning. Seize the opportunity to grow into an expert who discovers hidden patterns amidst volatility and makes wise, data-driven decisions.

In this course, you will understand the types and attributes of data and learn how to utilize descriptive and inferential statistics. Additionally, you will practice drawing data-driven conclusions by applying various statistical techniques, such as correlation and regression analysis, to real-world data. You can develop the practical skills needed to uncover meaningful insights within complex data.

Understand the basic principles of machine learning and deep learning, and learn about classification models and unsupervised learning algorithms. By identifying the characteristics of AI models using real-world data and looking into the history and future direction of AI, you will gain the insight to lead the data-driven AI era.


📚

Data-driven decision-making
competency enhancement curriculum

Section 1

Understanding Data and Its Types

Explore the essential meaning of data and learn about various data types and attributes. Through this, you will understand data structures and build a foundation for analysis.


Section 2

Foundations of Statistical Thinking

Learn the basic concepts of descriptive and inferential statistics and understand data analysis methodologies. Establish a core statistical thinking framework for data-driven decision-making.


Section 3

Relationship between Probability and Statistics

Understand the definition and necessity of probability, and learn core concepts such as conditional probability and independent events. Explore in depth how probability and statistics are interrelated.


Section 4

Principles and Application of Hypothesis Testing

Understand sample data and learn the principles and processes of hypothesis testing. Familiarize yourself with the limitations of hypothesis testing and precautions for practical application.


Section 5

Correlation Analysis

Understand the terminology and numerical values of correlations between data, and learn how to utilize correlation analysis. Identify potential errors and precautions to take when interpreting correlations.


Section 6

Regression Analysis and Prediction

Based on correlation analysis, you will learn the concepts and applications of regression analysis. You will build a foundation for predictive modeling using data.


Section 7

Machine Learning Overview

Learn the basic principles of machine learning and the characteristics of various data application fields. Understand the differences from statistical techniques and identify the types and characteristics of machine learning.


Section 8

Understanding Classification Models

Clarify the differences between prediction and classification problems and learn the core principles of classification models. Learn the metrics used to evaluate the performance of classification models.


Section 9

Unsupervised Learning Algorithms

Learn the major algorithms and characteristics of unsupervised learning, and understand the limitations of cluster analysis and precautions for interpretation. Master data analysis methods within an unsupervised learning environment.


Section 10

The Future of AI and Data

We will explore the history of AI development, its core functions, and the importance of data in depth. We will also look ahead to the future development of AI, which utilizes data as its primary material.


We can solve the concerns of
people like this!

📌

Corporate Business Leaders

Those who need data-driven decision-making but hesitate about what questions to ask when faced with complex statistical analysis results
Those who have difficulty accurately grasping the meaning of data and deriving clear insights

📌

Non-majors entering AI/Data Analysis

Those who know the importance of AI and data analysis but feel lost on where to start
Those who want to learn the basic principles of machine learning and deep learning easily so that even non-majors can understand them

📌

Developers participating in big data projects

Those who handle data in projects but feel they lack statistical thinking or data interpretation skills
Those who want to discover hidden patterns in data and effectively utilize analysis results for actual decision-making

Recommended for
these people

Who is this course right for?

  • Corporate executives and employees who need data-driven decision-making

  • Non-majors who want to equip themselves with AI and data analysis capabilities

  • Developers and practitioners participating in big data projects

Need to know before starting?

  • Basic business or work experience

  • Interest in data and AI, and a willingness to learn

  • Understanding of simple mathematical concepts

Hello
This is wendy34647345

Prime Contents Lab Co., Ltd. reads learning trends and designs its own courses. We constantly contemplate "who needs what." Based on the expertise of leading authors in each field, we create original educational programs ranging from IT/AI to the humanities that go beyond simple knowledge transfer to help achieve practical growth. Elevate your capabilities to the next level with the premium lectures proposed by Prime Contents Lab.

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Curriculum

All

50 lectures ∙ (3hr 32min)

Published: 
Last updated: 

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