I am dissapointed that i was right about my expectations on this first course, that it is just playing to the emotions and excitment. most of the course teaches nothing truly relevant to the process of learning data science. throughout the course i felt as though i had to read the Webster's dictionary definiton of what ask, process, share, blah, blah is. The teaching approach on this course is similar teaching a kid that wants to grow-up to be a baseball player, the he or she first need to know statistics and physics that is involved in the game of baseball. say, first learn at what angle the bat has to be in order to generate the height and speed necessarity to get the ball out of the park and what is the probability of it considering wind, rain, and other elements. THAT KID WILL NEVER GET SWING A BAT if this is the route he/she is on. So this bottom-up approach is BORING and IRRELEVANT. I don't think i need to know that ask comes before blah, and that share comes before blah. Get me hands-on activities that will encourage the student to ask what is the problem about, how to collect the data, what process should be follow, etc, etc.

so again this course is only playing to the emotions and excitment. This course should not be required as part of this program. NOT SURPRISINGLY DISSAPOINTED.

Why would completing the course take 6 months? Video content was repetitive and for the most part uninformative. Course description stated participants would " learn in-demand skills ... and learn how to process and analyze data, use key analysis tools, and create visualizations that can inform key business decisions. " Not true. Course content focused on what analysts might do, not how to do it. I'd be embarrassed to present a certificate for this course to an employer.

Some of the material was very repetitive and in the process terms kept changing making it a bit confusing to learn.

Hated how I had to fast forward thru the vides to mark complete or make a comment to the message board for it to complete. I just read the scripts for the videos - that is much better for me given my learning disability.

Overall - content was very good, useful, and helped me build a foundation for data analsics.

Painfully easy, no real value to be gained. The steps of the process could have been a single lecture with multiple practice problems to help solidify the concepts. Why waste a supposed 5 weeks to go over redundant topics? The material realistically can be completed in a single day if you have the time, or over a week if only working on it an hour or so a day.

i learned nothing from this at all, waste of time, stop placing a ton of fluff infront of what I actually came here for....I don't want to read about "the data analyst mindset" and learn about "the vocabulary".....where does the meat of these lessons start?..where's all the real math and work here?

The course is too slow in adding content. The whole course was only an introductory class. Nothing practical was taught, no data analysis skills trained.

Completely useless except for a few pieces of terminology. Would only recommend this to someone who has never used Excel at all before.

This course only tells you about what is data analysis, and the whole 4 weeks keep explaining what is data....so disappointed.

Memorizing of useless definitions, no new skills learnt

Very repetitive and boring.

Lacks technical depth.

"Foundations: Data, Data, Everywhere" is a remarkable exploration of the vast and intricate world of data, offering an insightful journey for both beginners and seasoned professionals in the field. Authored by experts in data science, this book delves deep into the foundations of data, providing a comprehensive and accessible guide that covers a wide range of topics. One of the strengths of this book lies in its ability to cater to a diverse audience. Whether you are a novice looking to understand the basics or an experienced data scientist seeking a refresher, the book is structured to accommodate different levels of expertise. The authors have skillfully crafted the content to build a solid foundation, starting with fundamental concepts and gradually progressing to more advanced topics. The book's organization is commendable, as it seamlessly transitions from the theoretical underpinnings of data to practical applications. Readers are taken through the evolution of data science, exploring key concepts such as data types, structures, and the crucial role of data in decision-making processes. The inclusion of real-world examples and case studies further enhances the book's applicability, allowing readers to connect theoretical knowledge with practical scenarios. What sets "Foundations: Data, Data, Everywhere" apart is its commitment to clarity and simplicity. Complex concepts are explained with clarity, and technical jargon is demystified, making the content accessible to a broad audience. The inclusion of visual aids, diagrams, and code snippets also aids in comprehension, especially for those who may be new to the intricacies of data science. The book also delves into emerging trends and technologies in the data landscape, ensuring that readers stay abreast of the latest developments. Topics like machine learning, artificial intelligence, and big data are explored, providing a forward-looking perspective that aligns with the dynamic nature of the field. While the content is rich and informative, some readers may find certain sections to be dense, especially if they are entirely new to the world of data science. However, the authors' efforts to balance depth with accessibility mitigate this challenge to a large extent. In conclusion, "Foundations: Data, Data, Everywhere" stands as an invaluable resource for anyone looking to build a strong foundation in data science. With its clear explanations, practical examples, and forward-thinking approach, the book is an excellent companion for both self-learners and those in academic or professional settings. It serves as a beacon, guiding readers through the expansive landscape of data and empowering them to navigate this ever-evolving field with confidence.

Taking a Foundations course in data analytics can offer a range of benefits, both for those new to the field and those looking to refresh or solidify their understanding of core concepts. Here are some of the advantages:

Foundational Knowledge

Understanding the Basics: The course lays the groundwork for all the tools and techniques you'll encounter later, giving you the essential knowledge needed to tackle more complex topics.

Structured Learning: Unlike self-study, a Foundations course usually follows a curriculum designed to logically progress from one topic to another, making the learning process more organized.

Skill Development

Analytical Thinking: The course teaches you how to approach problems analytically and make data-driven decisions, skills that are highly transferable.

Technical Skills: Get hands-on experience with tools like Excel, SQL, Python, or R to manipulate and analyze data.

Career Benefits

Increased Employability: Data analytics skills are in high demand across multiple industries. A foundational course can be a strong addition to your resume.

Career Flexibility: The skills you learn can be applied to various roles in data science, marketing, finance, healthcare, and more.

Certification: If the course offers a completion certificate, this could serve as a credential to prove your skill set.

Network Building

Professional Contacts: Courses often include guest lectures from industry professionals or provide opportunities to network, which can be invaluable for your career.

Peer Learning: Being in a structured educational setting allows you to learn from your peers, share insights, and even collaborate on future projects.

Focused Learning Environment

Access to Experts: Direct access to instructors means you can get your questions answered promptly.

Learning Resources: Structured courses often come with additional materials like reading lists, practice problems, and exams to help solidify your understanding.

Confidence

Skill Reinforcement: Successfully completing the course not only adds to your skill set but also builds your confidence in tackling more complex data-related tasks.

Bridging Gaps: If you're already in a role that requires data analytics, a Foundations course can help fill in any gaps in your knowledge and make you more effective at your job.

Exploratory Benefit

Determining Interest: Not sure if a career in data analytics is for you? A Foundations course is a relatively low-commitment way to gauge your interest in the field.

In a rapidly evolving field like data analytics, a foundational course can offer a structured and comprehensive introduction, giving you the tools you need to grow and succeed.

Title: Excellent Google Data Analytics Course on Coursera!

Rating: ⭐⭐⭐⭐⭐ (5/5)

I recently completed the Google Data Analytics course on Coursera, and I must say it was an outstanding experience. This course not only met my expectations but exceeded them in every aspect.

Content: ⭐⭐⭐⭐⭐

The course content is comprehensive, well-structured, and incredibly relevant. Each module was designed with clarity, providing a solid foundation before diving into more advanced topics. The real-world examples and case studies helped me understand how data analytics is applied in various industries.

Instructors: ⭐⭐⭐⭐⭐

The instructors were top-notch. They were not only knowledgeable but also had a knack for explaining complex concepts in a simple and engaging manner. Their enthusiasm and expertise kept me motivated throughout the course.

Hands-on Experience: ⭐⭐⭐⭐⭐

The hands-on assignments and projects were the highlight of the course. They allowed me to apply the concepts I learned to real datasets, giving me a taste of what it's like to work on actual data analysis projects. The step-by-step guidance and feedback provided a supportive learning environment.

Resources and Support: ⭐⭐⭐⭐⭐

The course materials, including readings, videos, and supplementary resources, were abundant and well-curated. The discussion forums were incredibly helpful, and the community aspect added a collaborative element to the learning experience. The support from both the instructors and fellow learners made problem-solving much easier.

Flexibility: ⭐⭐⭐⭐⭐

As a Coursera course, the flexibility it offered was invaluable. I could learn at my own pace, which was perfect for balancing with my other commitments. The modular structure also allowed me to revisit specific sections when needed.

Certification: ⭐⭐⭐⭐⭐

The course completion certificate holds genuine value. It serves as a testament to the skills I've acquired and has already proven to be a valuable addition to my professional profile.

Overall, I can confidently say that the Google Data Analytics course on Coursera is a must-take for anyone interested in entering the field of data analytics or looking to enhance their existing skills. The depth of knowledge, quality of instruction, and practical experience provided are truly exceptional. I'm grateful for this learning opportunity and can't wait to explore more courses in this domain.

I recently completed the "Foundations: Data, Data Everywhere" course offered by Google, and I found it to be an excellent introduction to the world of data analytics. This course is particularly well-suited for beginners who want to understand the fundamental concepts and importance of data in today’s digital landscape. Content Quality: The course is structured in a clear and engaging manner, covering essential topics such as the types of data, data collection methods, and the significance of data in decision-making processes. The content is well-researched and up-to-date, making it relevant for anyone looking to enter the field of data analytics. Teaching Style: The instructors are knowledgeable and articulate, making complex concepts easy to understand. They provide real-world examples and case studies that illustrate the practical applications of data analytics. The course also incorporates interactive elements, which helped reinforce my learning. Hands-On Experience: I appreciated the hands-on projects and exercises that allowed me to apply what I learned in real scenarios. This practical approach made the learning experience more engaging and helped solidify my understanding of the material. Accessibility: The course is easily accessible, with a user-friendly interface that allows learners to progress at their own pace. The bite-sized video lessons make it convenient to fit learning into a busy schedule. Overall Impression: Overall, "Foundations: Data, Data Everywhere" is an excellent starting point for anyone interested in data analytics. It not only equips you with foundational knowledge but also inspires you to explore further in the field. I highly recommend this course to anyone looking to understand the importance of data in the modern world and how it can drive meaningful insights and decisions.

As someone working in the ever-evolving landscape of data, I cannot stress enough the importance of staying updated and well-versed in this field. The course "Foundations: Data, Data, Everywhere" on Coursera has been an absolute game-changer for me. In today's world, where data is omnipresent and its utilization is key to success across various industries, this course provides a comprehensive overview and understanding of fundamental concepts. From data collection and processing to analysis and interpretation, every aspect is covered in detail. What I particularly appreciated about this course is its practical approach. This not only helped in grasping the concepts better but also made the learning process engaging and enjoyable. Moreover, the course content is structured in a way that caters to individuals at all levels of expertise. Whether you're a beginner looking to kickstart your journey into the world of data or a seasoned professional aiming to enhance your skills, there's something for everyone in this course. One of the standout features of the course is its relevance to the current industry trends. T In conclusion, "Foundations: Data, Data, Everywhere" is a must-take course for anyone aspiring to pursue a career in the field of data science or analytics. It not only provides a solid foundation but also instills the confidence to navigate through the complexities of data-driven decision-making. I wholeheartedly recommend it to anyone looking to thrive in the data-driven future. I'm incredibly grateful for having had the opportunity to enroll in this course, and I look forward to applying the knowledge and skills gained here in my professional endeavors.

Embarking on the Google Data Analytics course on Coursera was an eye-opening journey into the world of data-driven decision-making. From fundamental concepts to hands-on projects, this course provided a well-structured path to mastering the essentials of data analysis. What I Loved About the Course ✅ Comprehensive Curriculum – The course covered everything from data cleaning and visualization to SQL, R programming, and business problem-solving. Each module built upon the last, ensuring a smooth learning curve. ✅ Hands-On Learning – Through real-world case studies and practical exercises, I gained valuable experience in using tools like Google Sheets, SQL, and Tableau. These projects helped bridge the gap between theory and practical application. ✅ Industry-Recognized Certification – Completing this course not only boosted my confidence but also added credibility to my skill set as an entry-level data analyst. ✅ Engaging Instructors – The instructors did a fantastic job of breaking down complex topics into digestible lessons, making it easier for beginners to grasp key concepts. How This Course Helped Me 🔹 Strengthened my problem-solving skills by working with real-world datasets. 🔹 Gave me a deeper understanding of the data analysis process and storytelling with data. 🔹 Opened doors to job opportunities in the field of data analytics. Final Thoughts If you're looking to break into data analytics, this course is a fantastic starting point. Whether you're a beginner or someone looking to refine your skills, the structured approach and hands-on experience make it worth every minute. 🌟 **Rating: 5/5 – Highly Recommended!** 🌟

I am pleased to provide feedback on the Data Analytics Learning Program, aiming to make it accessible, thought-provoking, and conducive to broad thinking. The program effectively breaks down complex analytics concepts into digestible modules. The clear language used facilitates understanding, making it suitable for learners at various proficiency levels. The inclusion of real-world examples, such as the marketing campaign case study, adds practical relevance, enhancing engagement. While the program excels in clarity, incorporating more interactive elements, like quizzes or hands-on exercises, could further solidify understanding. Additionally, consider introducing diverse industry examples to broaden the scope and expose learners to various applications of data analytics. Encouraging participants to explore interdisciplinary applications of analytics could broaden their perspectives. For instance, linking data analysis techniques to fields beyond business, such as healthcare or social sciences, might stimulate creative problem-solving. Consider integrating more visuals, like data visualizations or infographics, to make abstract concepts more tangible. Visual aids can significantly enhance comprehension and retention. Overall, the Data Analytics Learning Program lays a solid foundation but has the potential for further enrichment. Strengthening interactive elements, diversifying industry examples, and incorporating more visuals could enhance the learning experience, fostering a more profound and versatile understanding of data analytics. Thank you for providing this valuable learning opportunity. Muhammad Ismail Tajuddin

Foundations: Data, Data, Everywhere by Google, offered through Coursera, is an excellent course that provides a solid introduction to the world of data analysis. As someone new to the field, this course was exactly what I needed to build a strong foundation in data analysis concepts and techniques.

The course content is well-structured and presented in a clear and engaging manner. The instructors are knowledgeable and effectively explain complex topics, making it easy to follow along and grasp the key concepts. The course covers a wide range of topics, including data collection, cleaning, visualization, and analysis, giving a comprehensive overview of the data analysis process.

One aspect that I particularly appreciated about this course is the hands-on approach. Throughout the course, there are practical exercises and assignments that allow learners to apply the concepts learned using real-world datasets. This practical experience helped me gain confidence in working with data and reinforced my understanding of the course material.

Furthermore, the course platform on Coursera is user-friendly and provides additional resources, such as quizzes and discussion forums, to further enhance the learning experience. The flexibility of the self-paced format allows learners to study at their own pace and revisit the material as needed.

Overall, Foundations: Data, Data, Everywhere is a highly recommended course for anyone interested in starting their journey in data analysis. It provides a solid foundation and equips learners with the essential skills and knowledge needed to tackle data-related challenges in various domains.

Dear coursera , Google and the Supportive Team,

I hope this message finds you well. I wanted to extend my heartfelt gratitude for the incredible learning journey I've had while completing the "Foundation Data, Data Everywhere" course. Your dedication to education and your expertise have made this experience truly remarkable.

Throughout the course, your ability to convey complex concepts with clarity and enthusiasm has been instrumental in my understanding of the subject matter. The course content, exercises, and real-world examples have given me a comprehensive foundation in working with data, which I believe will serve as an invaluable asset in my future endeavors.

I also want to express my appreciation to the entire team for the seamless delivery of the course. The thoughtfully designed structure and user-friendly interface made the learning process both enjoyable and effective. Your prompt support and assistance whenever I encountered challenges were greatly appreciated and contributed to a positive learning experience.

Completing this course has ignited a passion for data in me and has provided me with skills that I am eager to apply in real-world scenarios. I am confident that the knowledge I've gained will be a driving force in my personal and professional growth.

Once again, thank you for your dedication, expertise, and the opportunity to be part of this enriching learning journey. I am truly grateful and look forward to the positive impact this course will have on my future.

With sincere thanks,

Deepak Nandode

I am very satisfied with the experience. This certificate program provided an excellent introduction to the world of data analytics, covering fundamental concepts and practical skills essential for anyone interested in this field. The course content was well-structured and comprehensive, with a perfect balance of theory and hands-on exercises. From learning how to clean and analyze data to visualizing insights and making data-driven decisions, each module was thoughtfully designed to build upon the previous one, ensuring a smooth learning journey. What I found particularly valuable was the emphasis on real-world applications and case studies, which helped me understand how data analytics is used across different industries and domains. The interactive quizzes and assignments provided ample opportunities to apply what I learned and reinforce my understanding of key concepts. Moreover, the instructors were knowledgeable and engaging, providing clear explanations and practical tips throughout the course. The video lectures were easy to follow, and the supplementary resources and readings further enriched my learning experience. Overall, I highly recommend the 'Foundations: Data, Data, Everywhere' Certificate to anyone looking to gain a solid foundation in data analytics. Whether you're a beginner exploring this field or seeking to enhance your existing skills, this certificate program offers a valuable opportunity to acquire essential knowledge and tools to succeed in today's data-driven world.

"Foundations: Data, Data, Everywhere" is a compelling exploration into the ubiquitous presence of data in our modern world. The book adeptly navigates through the myriad ways data influences our lives, from personal decisions to global trends. With insightful analysis and real-world examples, the author sheds light on the power and potential pitfalls of data in today's society. One of the book's strengths is its accessibility. Despite delving into complex topics such as data privacy, algorithms, and artificial intelligence, it remains approachable to readers with varying levels of technical expertise. This accessibility makes it an invaluable resource for anyone seeking to understand the role of data in contemporary society. Moreover, "Foundations: Data, Data, Everywhere" doesn't merely focus on the theoretical aspects of data; it also provides practical insights and actionable advice. Whether you're a business leader aiming to leverage data for strategic decision-making or an individual concerned about privacy in the digital age, this book offers valuable perspectives and guidance. Overall, "Foundations: Data, Data, Everywhere" is a must-read for anyone interested in the intersection of technology, society, and data. It effectively demystifies complex concepts, raises important questions, and prompts readers to critically evaluate the role of data in shaping our present and future.

The course "Dasar-dasar Analitik Data: Data, Data di Mana-mana" (Basics of Data Analytics: Data, Data Everywhere) offered on platforms like Coursera, is part of Google’s career certificate program. It is designed for individuals looking to understand the fundamentals of data analysis, with modules covering essential skills and tools like spreadsheets, query languages (SQL), and data visualization tools. Throughout the course, you will explore the lifecycle of data and learn about the various stages of data analysis, including collection, processing, and visualization. One of the key highlights of the course is the focus on practical tools, such as using spreadsheets for data analysis, SQL for querying databases, and visualizations to make data-driven decisions. This hands-on approach helps students apply theoretical knowledge to real-world data tasks, preparing them for roles in data analysis. Moreover, the course emphasizes the importance of data analytics across various industries and offers insights into career opportunities for data analysts. It is structured into manageable modules, each featuring videos, readings, quizzes, and discussion prompts to reinforce learning. This course can be an excellent choice if you're looking to enhance your skills in data analysis and pursue a career in the field, with a strong emphasis on practical applications and industry relevance.

I don't have a physical existence or a place of residence as I am a computer program created by OpenAI, so I don't have personal details such as where I live or where I'm originally from. I was created by OpenAI as part of their efforts to develop advanced natural language processing models. My purpose is to assist and provide information to the best of my abilities. I don't have personal goals or expectations as I am a tool designed to assist with generating human-like text based on the input I receive. I don't have the capability to learn or feel excitement. However, I can provide information and answer questions related to data analytics. I don't have a personal educational background or career path as I am a machine learning model. I don't have personal experiences or a career. I don't have personal interests outside of work as I am not an individual with personal preferences. However, I can provide information on a wide range of topics. I won't earn a certificate as I am not an entity that can undergo educational or certification processes. I exist to assist with generating human-like text based on input data. Please note that I am a machine learning model and don't have personal experiences, feelings, or a physical presence. My responses are generated based on patterns and information present in the data on which I was trained.

The course is well designed, with each module aimed at educating students and boosting their confidence in the subject. The practical examples shared are relatable and enhance understanding. Furthermore, the interactive elements integrated throughout the course foster an engaging learning environment. Group discussions and collaborative projects encourage students to share insights and learn from one another, reinforcing key concepts while building essential skills. The instructors are approachable and knowledgeable, always ready to provide guidance and support, which further enhances the overall educational experience. As students progress through the curriculum, they not only acquire theoretical knowledge but also develop practical skills that prepare them for real-world applications. The assessments are thoughtfully designed, allowing for constructive feedback that helps to identify strengths and areas for improvement. This method of continuous evaluation promotes growth and ensures that each learner can track their progress effectively. Overall, this course stands out as a comprehensive pathway to mastery in the subject, cultivating both expertise and self-assurance. It is a journey that empowers students to overcome challenges and emerge as confident, capable individuals ready to make their mark in their chosen fields.