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DATA 101: The Fundamental Building Block of AI Systems.
7 students
DATA 101: The Fundamental Building Block of AI Systems.
Learn the True Nature, Behavior and Characteristics of fundamental building block of Artificial Intelligence.
Created byOsman Mohammed, Abdul Bari Mohammed
Last updated 1/2024
English
What you'll learn
- Understand the fundamentals of data: By the end of the course, students should be able to explain what data is, its history, and its importance in the modern wo
- Differentiate between types of data: Students will learn to distinguish between various types of data (qualitative, quantitative, structured, unstructured) and
- Recognize and interpret data formats and representations: Students should be able to identify common data formats (such as CSV, JSON, and XML) and interpret dat
- Comprehend the life cycle of data: Students will understand the various stages in the data life cycle, from collection and storage, to processing, analysis, and
- Evaluate data quality and value: Students will learn to assess the accuracy, consistency, completeness, and relevance of data, and understand the costs and bene
- Understand the impact and applications of data: By the end of the course, students should be able to discuss the impact of data on businesses, society, and indi
- Anticipate the future of data: Students will explore emerging data technologies (such as AI, ML, and IoT), and discuss predictions, trends, and ethical consider
- Develop data intuition and literacy: By the end of the course, students should have developed a data mindset, learned key data literacy skills and tools, and be
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Course content
9 sections • 19 lectures • 1h 34m total length
Requirements
- Basic Computer Literacy: You should be comfortable using a computer, browsing the internet, and working with files and folders.
- Mathematics Knowledge: Some sections of the course may require a basic understanding of statistics and probability, although we'll try to keep this accessible for beginners.
- Software: Depending on the specific sections of the course, we might work with specific data analysis or visualization tools. Familiarity with any data-specific software is a plus, but not required. We'll introduce necessary tools and provide guidance on their usage during the course.
- Curiosity and Open-mindedness: This course is designed for anyone eager to understand the fascinating world of data. All you need is a willingness to learn, ask questions, and explore various aspects of data.
- Time Commitment: Be prepared to dedicate some time outside of the lessons for self-study and exercises. The more you put into practice what you've learned, the more you'll get out of the course.
Description
1. Welcome & Instructor Intro
Hello Everyone, Welcome to the course "The Complete Software Engineering Mastery Bootcamp 2023."
My name is Osman Mohammed, and I'll be your guide on this transformative journey.
I'm currently employed at one of the BIG-4 Consulting firms, bringing over 8 years of hands-on experience in Software Engineering. I've been involved in Designing, Developing, and Maintaining both web-based and standalone Software Systems.
I've had the privilege of working across various software development life cycles, including Waterfall, Agile, DevOps, and DevSecOps.
I hold a Master's Degree in Computer Science and Information Technology and am currently diving into the fascinating world of AI Alignment Problems.
I'm thrilled to be collaborating on this course with my elder brother Abdul Bari Mohammed, who serves as a Lead Quality Engineer at Amazon.
2. Course Outcome
This course is meticulously designed to transform you into an impactful Software Engineer. By the end of this course, you'll have a comprehensive understanding of Computer Science and Information Technology fundamentals, testing methodologies, version control, real-world project execution, and many more. This knowledge will empower you to adapt to emerging technologies and understand how software engineering shapes various industries.
3. Ideal Students for this Course
This course is perfect for anyone—whether you're a complete beginner or someone looking to deepen your understanding of software engineering. No prior experience is required; all I ask is that you bring an open mind and a thirst for knowledge.
4. Thank You & Please Enroll
I'm genuinely excited to embark on this educational journey with you. Your future as a Software Engineer starts here, and I can't wait to see where this course takes you. Please enroll, and let's get started!
Who this course is for:
- This course requires no prior experience in data and is designed to be accessible to anyone with a desire to learn. If you're interested in the role data plays in our world and want to develop a deeper understanding of it, this course is for you.
- Beginners in Data Science or Analytics: If you're just starting your journey in the data world and looking to build a strong foundation in understanding data, its types, lifecycle, impact, and future, this course will give you the comprehensive overview you need.
- Professionals in Other Fields: Professionals from various fields such as business, healthcare, government, education, etc., who want to leverage data for better decision-making, will find this course beneficial. It will help you understand how data can provide insights and drive impactful decisions in your field.
- Aspiring Data-Literate Individuals: In today's data-driven world, being data literate is an essential skill. Whether you're a student, a job seeker, or just a curious individual, this course will help you become more comfortable with data, improving your data intuition and literacy.
- Entrepreneurs and Business Leaders: If you're an entrepreneur or a business leader, understanding data can help you make informed decisions, identify trends, and drive success. This course will provide the knowledge you need to harness the power of data in your business strategy.
- Educators and Academic Researchers: Those involved in teaching or research can leverage this course to understand how data is transforming our world, enabling them to better educate others or to use data effectively in their research work.