good

Good

PACE

good

Good

good

Nice

good

nice

very

Good

5

.

D

I'm thrilled to share that I've successfully completed the first part of the Google Advanced Data Analytics Certification course, "Foundations of Data Science"! 📊🔍During this comprehensive program, I've gained a deep understanding of the core concepts, tools, and techniques used in the field of data science. From data exploration and visualization to statistical analysis and machine learning, this course has equipped me with the essential skills needed to derive valuable insights from complex datasets.I want to express my gratitude to Google for offering this remarkable learning opportunity and providing an exceptional curriculum. The course was challenging yet highly rewarding, pushing me to expand my analytical thinking and problem-solving abilities.I'm now more confident than ever in my ability to tackle real-world data challenges and make data-driven decisions that drive meaningful outcomes. 📈💡I would like to extend a special thanks to my instructors and fellow classmates who contributed to the collaborative and engaging learning environment. It was a pleasure to connect with professionals from diverse backgrounds, all passionate about leveraging data for positive change.I'm excited to continue my journey in the Google Advanced Data Analytics Certification course, as I delve deeper into the intricacies of advanced data analytics and gain expertise in topics such as BigQuery, machine learning algorithms, and data visualization.If you're interested in the exciting world of data analytics and the power it holds to transform businesses, I highly recommend exploring this certification program offered by Google.

The course did generally do a good job of providing necessary background knowlege about data careers and setting the pace for the upcoming courses. The only little thing I found that got annoying was for the final quarter of the course where things seemed to get a bit repetitive. Sane concepts about the PACE workflow were being repeated over and overagain in seperate reading and videos. I understand that the concepts being explained were important so it was important to reiterate but I think they wre reiterated a bit too much. Think the course can shave a few hours of without the unnecssary repetition. Overall though I really did find thhe course very helpful which is the most important thing.

Hi everyone,

This is honestly a great class, but it felt like a summary of the previous Google Data Analytics Certificate. In fact, I found myself having to speed up the videos since I just reviewed most of it.

Overall though, one very nice aspect about this course over the previous certificate was that you dive into job opportunities and projects right away. I thought that that was a much better option instead of having to wait until the end of the course like the original.

Can't wait to do class 2!

-Steven A. Monserrate

I did like most of the material and I liked that the course puts the job of a data analyst in a context by also introducing not technical aspects of the job. However, although the course seems to be gathered for data analysis, the instructors and the examples throughout the course mentions mostly data scientists, which becomes annoying after a while. The course seems to be too "introductory" to prepare yourself fully for a data science role, and still this role is brought up consistently throughout the lectures.

While the course was engaging and interesting I find it a little strange that we are being taught about networking, mentorships, and LinkedIn profiles at the start of a course designed to give real world skills for data analysis. Landing the job is important but I feel like this content should be an optional final course for the advanced certificate. Quality of content was good, readings were up to date which is a change from a lot of online courses.

Informative course on the spectrum of data science, the different roles of data scientist and their standing in a data team. I'm impressed that this heavily emphasizes project management and communication at the very beginning. However, 4 star is rated because there are a lot of readings in a row. I prefer reading to videos, but I also got tired reading a ton and resorted to AI summary later in the course.

A well made foundational cource about the data career workflow. How a data project is carried out and other important skills needed in the workspace for a success in the project are discussed. With a focus on on interpersonal skills this cource also covers the data career market space & skills that would help standout more & land your first jobin the data field.

While the course builds a great foundation for anyone entering the data-career space, sometimes it goes a bit beyond the limit into the details that might not have been necessary to understand fully at the moment. Overall, it was a decent course and it surely helped me gain a little more interest in the data analytics.

It's really important to know how a data project is developed inside a company, the data stategy and more. Maybe you can make it more professional and maybe show real cases examples of the past or something like that. Showing how a project was developed from the begining it can be really insightful.

The material about PACE in module 5 does not align with the strategy document in the Course 1 project. For ex: the PACE strategy document exemplar in the project identifies some tasks that they belong to multiple stages, but the material does not make that immediately clear.

It was interesting to know the wide range of opportunities and the foundational skills required for each. The course is structured well and informative supporting material are provided. Excited to continue with the rest of the courses in this certificate programme