Melina A.
Before 365:
Information Design | UAM
After 365:
Data Analyst | TELUS Digital
See all reviews
Online Course
bestseller
Introduction to Data and Data Science
with
Martin Ganchev
and
Iliya Valchanov
This data science fundamentals course is the perfect introduction to the field. Gain an overall understanding of data analysis, machine learning, and statistical techniques. Learn how data science helps businesses solve real-world problems
243067 students already have enrolled
Skill level:
Basic
Duration:
3 hours
-
Lessons (2 hours)
-
Practice exams (26 minutes)
- Lessons (2 hours)
- Practice exams (26 minutes)
CPE credits:
6
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
Accredited:
certificate
What You Learn
- Acquire a clear overview of modern data science fundamentals.
- Explore how analysis and data science deliver business value.
- Learn key terminology and core data science concepts.
- Grasp the intuition behind business intelligence and machine learning methods.
- Identify data science roles and career path opportunities.
Topics & tools
theorydata analysisprogrammingcareer developmentdata literacy
Your instructor
Content Creator & Content Manager at 365 Data Science | Data Science Instructor
Track record
Bringing real-world expertise from leading global companies
Academic background
Master's degree, Economic and Social Sciences
CEO of Team-GPT | AI Educator | Co-founder of 365 Data Science & 3veta
Track record
Bringing real-world expertise from leading global companies
Academic background
Bachelor's degree, International Economics, Management, and Finance
Course OVERVIEW
Description
CPE Credits: 6
Field of Study: Information Technology
Delivery Method: QAS Self Study
Delivery Method: QAS Self Study
Are you looking for a well-structured data science fundamentals course?
Do you want to gain a clear understanding of the data science field?
This is the perfect course for you!
If terms like ‘traditional data,’ ‘big data,’ ‘business intelligence,’ ‘business analytics,’ ‘data analytics,’ ‘data science,’ and ‘machine learning’ sound confusing, then taking this data science fundamentals course will help you understand the meaning and practical application of these concepts—making you proficient in the language of data.
These skills can boost anyone's career. We live in the age of AI, but few people realize that data science fundamentals are the foundation upon which AI is built.
This course is suitable for aspiring data analysts and data scientists. Still, it’s also highly recommended for business executives and professionals to enhance their understanding of data-driven decision-making.
Embark on a journey through the various domains of data science—exploring the connections among them for a comprehensive understanding of the field. You’ll soon comprehend the business and analytical motivations behind specific analyses and the necessity of data science.
Additionally, you'll discover the techniques and tools data analysts and data scientists employ to analyze data effectively.
If you're considering a career in data science, this course is invaluable because it clearly and thoroughly introduces various data science roles. Completing it will clarify who does what and help you identify the role that matches your career aspirations—setting a clear path to your goals.
What sets this data science fundamentals course apart from others? Several key differences exist:
1. Exceptional Content Quality
Our team has spent thousands of hours to create the best learning experience for you. We develop content full-time, invest significant time to digest complex topics quickly and design a pleasant learning journey.
2. Top Online Data Science Intro Course
This course has become one of the most popular online courses on data science fundamentals. For example, one of the course’s flagship resources (365 Data Science Infographic) has been shared over a thousand times on LinkedIn. Over a million students worldwide have chosen this course and rated it excellent.
3. Engaging Animations
Learning visually is one of the best ways to understand complex topics such as data science, machine learning, and deep learning. Internalizing practical concepts is much easier when you have seen high-quality visual examples. Our courses feature stunning animations—far beyond basic PowerPoint slides.
4. Innovative Interactive Exercises
Our platform's innovative, interactive exercises help you consolidate your learning effectively. Experience the best of hands-on learning in this data science fundamentals course.
5. Comprehensive Downloadable Material
Explore essential data science resources, including course notes, key term flashcards, infographics, diagrams, and practice exams—all available within the course for easy reference.
Prerequisites
- No prior experience or knowledge is required. We will start from the basics and gradually build your understanding. Everything you need is included in the course.
Advanced preparation
- None
Curriculum
25 lessons
57 exercises
4 exams
- 2. The Relationship between Different Data Science Fields7 MinIn this section, you will learn how data science fields relate to each other and which ones leverage on traditional and big data, business intelligence, or traditional data science methods and machine learning.
- 3. What is the Purpose of each Data Science field4 MinHere, you will learn not only which are the various data science disciplines, but also what each discipline is used for in practice. This is really valuable for you, as it will allow you to gain an idea of the practical application of the different methods you will learn later on in our program.
- 4. Common Data Science Techniques60 MinThere are different ways to approach traditional data, big data, business intelligence, traditional data science methods, and machine learning. In this part of the course, we will introduce you to some of the most common techniques to do that, and we will provide several practical examples that will make things easier and more relatable.Traditional Data: TechniquesExerciseTraditional Data: Real-life ExamplesBig Data: TechniquesBig Data: Real-life ExamplesExerciseBusiness Intelligence (BI): TechniquesExerciseBusiness Intelligence (BI): Real-life ExamplesTraditional Methods: TechniquesExerciseTraditional Methods: Real-life ExamplesExerciseMachine Learning (ML): TechniquesExerciseMachine Learning (ML): Types of Machine LearningExerciseMachine Learning (ML): Evolution and Latest TrendsExerciseMachine Learning (ML): Real-life ExamplesPractice examExercise
- 5. Common Data Science Tools6 MinBefore we dive in to studying the different types of tools used in data science, we will provide a quick overview for you, so you can have a good idea of why we are studying different tools and how they interact with each other. This will greatly facilitate your learning process, as you will already know what to expect and which tools will be necessary for a specific task.
- 6. Data Science Job Positions: What do they Involve and What to Look out for?3 MinIn this section, we will discuss several job positions related to the fields of data and data science, including what responsibilities they’re comprised of and what to look out for when choosing your path.
- 7. Dispelling common Misconceptions4 MinWe will conclude our Intro to Data and Data Science training with a lesson that dispels the most common misconceptions about the field of data science.
- 8. Course exam30 Min
Free preview
1.1 Course Introduction
3 min
1.2 Why are there so many business and data science buzzwords?
5 min
1.4 Analysis vs Analytics
4 min
1.6 Intro to Business Analytics, Data Analytics, and Data Science
7 min
1.8 Adding Business Intelligence (BI), Machine Learning (ML), and Artificial Intelligence (AI) to the picture
9 min
1.14 An Overview of our Data Science Infographic
4 min
96%
of our students recommend
365 Data Science.
94%
of AI and data science graduates
successfully change
or advance their careers.
9 in 10
of our graduates landed a new AI & data job
after enrollment
ACCREDITED certificates
Craft a resume and LinkedIn profile you’re proud of—featuring certificates recognized by leading global
institutions.
Earn CPE-accredited credentials that showcase your dedication, growth, and essential skills—the qualities
employers value most.
Certificates are included with the Self-Study learning plan.
How it WORKS
Student REVIEWS
