TripleTen

Practicum is great. I don't think it's 100/100 but it closes in 95 or above for sure. The information gets to the heart of what software engineering is about and I think they do a fantastic time with giving yo the tools in order for you to solve every problem. They hold your hand just enough in the beginning to get your pace set us but you very much have to be self motivated because you won't finish or hit your deadlines if this isn't your endgame. The best part of Practicum aren't their lectures but the community. You get access to many skilled tutors and they host office hours and can help you with your questions and concerns, this is priceless especially when starting out because coding isn't the easiest of tasks. I would recommend practicum to anybody.

In my time in Practicum's Data Science bootcamp I have developed a good understanding of the Python pandas library and how to use it to manipulate and look into data files. The learning pace is quick, and to stay on track you must spend a good amount of time per week studying and reviewing the coursework. I am still attending the bootcamp while working a full-time job, which is certainly challenging, but if you have the desire and motivation to learn data science then you can make it happen. If you have any questions or problems with the coursework or the projects, there are tutors and instructors that are available every day throughout the week that will happily assist you. There are also learning sessions every Saturday where instructors will go in-depth into the course material and show some different examples of how to use what you've learned throughout the bootcamp. Practicum makes all the resources you need to do well available, it's up to you to use them to your advantage and help develop your learning and knowledge of the subjects. My community manager checks in with me often and makes sure that I can access what I need for learning easily and readily, and regularly offers reminders about opportunities for communication with tutors and instructors. Practicum's cost for the Data Science bootcamp was very reasonable, especially after working out a 30% discount with the recruiter. The job acceptance statistic was very attractive too, one of the major reasons why I chose Practicum for my Data Science training. 

The most valuable part of this bootcamp was the abundance of group collaboration projects you get to sign up for and gain experience from. In all my tech interviews, I was able to bring up these valuable team work experiences and stand out from the rest. Team work is very important in this field and only having solo projects in your portfolio isn't the optimal way to go. 

Practicum has code jams, apiary projects, pair programming, senior students and other opportunities you can work with others in coding. The curriculum itself is very comprehensive as well, given 10 months. I felt very confident in my skills upon graduation, especially with my frontend skills including vanilla CSS, vanilla JS and React.

One thing I will point out is that this bootcamp may be very challenging if students enroll without any prior knowledge of programing or basic computer literacy. You will be asked to work with command lines, terminals, git right away. I also see lots of people struggle with JS and responsive design. This is not a handholding bootcamp where things will be fed to your mouth. Utilize the resources you have and try your darn best to work hard, and then this will be a blast.

My interest in data science started after my early introduction while studying for my engineering degree. After the completion of my degree, I decided to break into the data space and did a bit of self-learning using multiple resources available online. I came to the quick realization that I need a structure to guide my learning and also curate what I really need to know, without trying to understand everything that there is out and getting into a rabbit hole. The bootcamp covers all skills you will need and libraries for the data science projects; from data gathering, data cleaning, data exploration, model building and training and finally model validation, all of this in the context of business value. This was a structure that practicum provided. The additional service of code review by industry data scientist was also an important part that validated my skill set and morale boost. Each module was well explained and expanded, and I saw the value in this having tried to study using other resources. However, the specialty modules (nlp, computer vision and deep learning) in my opinion are introductory, understandably so and for students with an interest in these field; additional study will be required to build on the basics taught in the boot camp. The community on slack were very professional, quick to respond to any learning concerns and questions about the projects and other personal projects. 
 Overall, practicum has been valuable in my journey to become a data scientist

How it startedAre you looking for a program that is quick, and easy? This isn’t the path for you. Deciding to join a field I have no experience or knowledge in, is one of the most difficult and rewarding choices I’ve made. I started this mission at a point in my life where I wanted a challenge, to see what I was capable of. I needed to find a program that would facilitate this challenge. I wanted an education that could offer me more than PowerPoints and mandatory Zoom lectures. Dedication is required, if you want to succeed in this bootcamp. The motivational speaker T. Harv Eker said it best, ““The only time you are actually growing is when you are uncomfortable.”
Why PracticumI did my research to see what made Practicum different from other programs, and I highly suggest you do the same. This program introduces what a Data Analyst does, by teaching skills in a realistic project format. Unlike most programs, we don’t take tests. We work at our own pace. A general calendar is given, but it’s only to help us stay on course. There is no grading scale. 
I wondered, how is the program structured? Our goal is to complete lessons on an interactive platform and apply those lessons to a project. It’s broken down into manageable chapters, and further broken down into lessons.  You project is reviewed, comments are left, and you have unlimited opportunity’s to fix and resubmit it. It’s very stress-free, and the reviewer offers guidance and suggestions. They are very encouraging. 

What does a Data Analyst do?I gathered general information about the purpose of a Data Analyst: identifying efficiencies, problem areas, or possible improvements for businesses. We learn what it means to import, inspect, clean, transform, validate, collect process and interpret data. But what does that mean? The best way to understand is with a real life example. If a gaming company wants to develop a marketing strategy, they hire a data analyst. They would provide visual reports as to which factors have the highest impact on revenue: is it genre, is it rating, maybe platform??  We learn how to pick up trends in the data. 
With the ability to code, we learn to answer complex business decisions. This program also gives us access on how to acquire data, to answer those questions.

Can I do this?I had no idea what a data analyst was, all I knew was they can work remotely and make good money. A huge question I needed to know: “Do I need a college degree to be a Data Analyst?” The answer is: No!! But you might want to refresh your functions and statistics skills. You’ll be able to lean on tutors, StackOverflow, and Youtube for support. 
Another question I asked: “Are they hiring remote jobs that pay well?” I continue to check daily, and yes!! I have the privilege of narrowing down the companies, based on the type I want to work for. 
They are motivated to help you find a career.  My main skepticism was their price to take the course. Why is the program significantly more affordable than others like it? Practicum is still relativity new - which means the students are helping them develop and improve the user experience. 
I didn’t recognize any of the subjects listed in the program that I would be learning. Before I started, I wondered, “Will I succeed if I have NO experience?” The answer is, YES!!! I look at it like I’m learning a new language. I don’t consider myself a fast learner, however I am able to keep up with the pace. The tutors offer zoom meetings, you can share your screen and receive guidance. Often, they teach me insider tricks, tips, and hacks, that only come from working experience. I learned to focus on the concepts, rather than trying to memorize the code. Data Analysts often have resources they refer to when working on projects.
Communication Slack is a messaging platform that Practicum uses. We use this to communicate with our tutors, community manager, professor, and other students.  You can see what other students ask, or ask your own questions. This has been a great resource when I’m stuck on an error, or need an extension. I also use the support chat within the lesson I am working on. If your error is simple, they are able to help you quickly.
Program SupportThis program is designed to help students succeed. It’s very hard, which I’ve learned to appreciate.  I will admit, there are moments during this course that I’ve doubted myself. It felt as though I was not able to absorb all this new information. A tutor convinced me to trust the process, telling me it was slowly begin to become second nature. No matter how hard I am struggling:  I can always get more time, I can always get more help, and I am never alone. I put my skills to the test when we did our Integrated Project. I was able to recall and apply the new information I once found impossibly challenging. 
Anxiety contributes to why I have not had success with traditional online programs. Deadlines often discouraged me, fearing my lifestyle would interfere with meeting them. Practicum is flexible. The community manager is REALLY going to help you. When a particular “sprint” is difficult, I’ve been given one week extensions for extra time and support.  Also, they offer students breaks. I was able to take a week off from my studies without falling behind. The team at Practicum encourages you to take these extensions and breaks when you need them. 
The extensions and breaks made the largest impact on my success. The supper they offer, and the way they communicate that support, is the number one reason I recommended this program over others that offer similar skills. 
Career Support The projects you’ve created are resources for a resume. They provide realistic tasks you could expect to perform for a client or company. Data workers are in high demand, because coding is a valuable experience to most employers. As it continues to grow, the STEM field is in high demand of workers. This career is versatile, there are many different career paths you can transition to: software engineering, data scientist, etc. Joining a STEM field is a safe investment with my future.

I decided to start my data science career after graduating in Engineering. Back then, I had average coding skills, although completely new to Python, and some decent Math background. I looked forward to a course that would be suitable to my level and that would help me start working in this career. After carefully searching online and reading through reviews of courses in this same Course Report website, I ended up picking Practicum, and now that I am about to finish this course, I am very satisfied and happy with my choice!

Practicum came as a cost-efficient option that would also give me the choice of learning at my own pace if needed. I had a demo of the first Python sprint before entering the course, which is a complete basic course and is a great way to test the platform before enrolling. I was surprised at how the topics were explained in a concise and efficient way, while making sure I was understanding the practical aspect of what I was learning. After this great initial experience the difficulty increases with each sprint, and although I had previous knowledge in some chapters, there were still challenging new topics to learn. The explanations are mainly text and questions to answer and they feel very dynamic, with graphs, images and step-by-step coding practices. Support is always a click away, while questions about the learning material can be asked to tutors available on the Slack channels. The whole staff and environment is very welcoming and I sincerely admire the teaching methods of tutors to prepare for jobs later on.

At the end of each sprint, there is a project that helps in grasping what was learned and adds to the list of projects developed by the student, and these are really the best part of the bootcamp. That's when students start communicating on the Slack channels to ask questions about the challenging parts of the project. Projects are developed in the practicum platform app and there are also weekly webinars aimed to help students, and they mimic real-world tasks. There are also weekly webinars to expand on specific topics about Data Science, and that's a nice way to get to meet other students.

Practicum also provides a Career Prep course, but before I finished the bootcamp I started working as a researcher in an university, so I haven't started it yet. The Python skills I learned were more than enough to start working as a Python developer, and I noticed that even some of my colleagues did not know some resources that I had learned. I generally feel confident and motivated to keep growing my Data Science career. I still intend to attend the Career Prep course and then I will be able to complete this review.

I come from an entertainment background, but I’ve always been interested in potentially working in a tech field/industry. I’ve also always been somewhere who has a natural curiosity about data and the information that can be derived from it. After thinking about it some, I decided to pursue an online program in data analyst. This allowed me to still be able to work part-time without having to change my work schedule.  I researched many programs, but I eventually settled on Practicum as it offered the most value for the cost. I was also very intrigued by the opportunity to work with real companies and then have those companies vouch for you on websites such as LinkedIn. Practicum also had the most unique set up with a dedicated platform to work on the coding and theory. This allowed for hands-on practice and repetition which allowed me to retain the material. The projects at the end of the module also helped solidify the skills I just learned and how they could be applied in a real-world setting. Additionally, these projects aided in building my portfolio. I’m nearing the end of the program now and I’ve been exposed to many of the skills required for a Jr. Data Analyst position and I feel equipped to apply to jobs once I finish the program. The Slack community was also crucial in aiding me overcome coding challenges when working on the tasks or projects. It also helped in seeing how people have different coding styles, but the end result is the same. Practicum also offers a Career Prep course that I am also enrolled in. I’m not done with it yet but what I’ve seen so far is a good indicator that the Prep Course will indeed be helpful when it comes to learning how to build an online network. 

I started the Data Science program at Practicum about 6 months ago (it is a 9-month program). I can say that 6 months later, I feel that I have learned a lot! I started the program because I wanted to make a change in my career path that I felt would challenge me in ways that I have not been challenged before and to acquire a job that best suits my lifestyle as a mom of 2. My background is in psychology and academic tutoring, so it was a pretty significant shift going from that to data science. That being said, I have always been very passionate about data and statistics, which led me on the path to discover the relatively new world of data science. Being a mom of 2, I knew that taking the formal education route again (I already had a Bachelors degree) was not going to be a viable option time-wise or financially, so I started looking for online programs that offered a fast but concentrated training without breaking the bank. I researched several other online programs before I discovered Practicum, but ultimately I chose practicum because it was cost-effective, it's expertise and curriculum was rated highly, and because they guarantee job placement in your field within 6 months of graduation. Six months into the program, I could say that this program definitely provides a solid foundation of training in data science. The learning platform provides a flexible way to learn the material, and each cohort has tutors that we can access regularly with any questions. I will say the only con is that although the curriculum is challenging it can sometimes be unclear how to solve certain assigned tasks within the chapter. Nevertheless, the tutors are usually available to provide extra explanations as to how to go about with the solutions. When I first started the program, I found that delegating about 15-20 hours a week studying was sufficient to move along at a steady pace. However, as the topics become more advanced I find myself dedicating about 30 hours or so a week completing material and projects. So, although the program is online, you should still expect to dedicate several hours toward it a week if you intend on staying on track. I am nearing graduation in a few months, which I am very excited about! I feel as though I went from knowing nothing about data science to being able to understand theoretical and practical applications of data science. In this way, I feel that Practicum is preparing me for a career in data science. I look forward to being able to apply everything this program has top in my job in the future! 

Taking this Data Science bootcamp was undoubtedly the best choice to make in my career path. As a Finance and Accounting professional, I wanted to take my data analysis skills to the next level and had previously tried to learn Python for Data Science autonomously, but was lacking the right structure to progressively gain sufficient knowledge so as to be able to complete an end-to-end project, being fully aware of the underlying mathematical foundations each ML model is based on. 
At first, I wasn't really sure whether I would be able to commit 20 hours a week on top of my 40 hours workload, but fortunately, decided to challenge myself to do so. The whole Practicum team, from the Community Managers to the tutors, are always willing and happy to help with anything that may pop up, making the programme fit your own schedule and prioritizing the goal of building up a solid understanding of each sprint content over forcing students to meet strict deadlines. I would definitely recommend this course to anyone aiming to break into the industry on the right footing.

I was looking for a place which would allow me both working at a full-time job and boosting my Data Science career, which I have transferred to after being a Business Analyst for 10+ years. Although, back then, my professional life started with wealth of data analysis, I had been focusing more on entrepreneurship, operations, and regulation throughout my career; thus, at the very beginning, as a Data Science professional I faced plenty of challenges: given how fast the overall industry of Data has been developing for the past 10-15 years, I figured out that I had enough gaps to bridge and that I needed some guidance. I was introduced to Practicum by my ex-colleagues and decided to check it out. I realized eventually that both the Data Analyst and the Data Science courses are packed with state-of-the-art content and overall approach is sprint-based, so I decided to sign up for both of them and make the DS course just after graduating from the DA course. The Practicum community managers navigated me through all the organizational questions, so I could just continue enjoying seamless learning experience, so now I am three months left until my graduation from the Practicum Data Science course.

Now, straight to the point. Beyond the outstanding UI, you can literally feel how much effort was invested in the course content development. With Practicum, you get a very clear roadmap: all the sprints are well structured as collections of short lessons, where the next one builds upon the previous one, while every lessons provides practical exercises, both as part of the theoretical part and when you finish going through the theory. By the way, there are several lessons devoted to developing your soft skills, which impressed me so much: those pieces of wisdom are absolutely invaluable!

Projects are at the center of the learning process; they are the best way to gain valuable hands-on experience, since a thorough code review gently points out the ways you can make your code better; on top of that, tutors encourage you to keep trying additional techniques/alternatives and provide references to upgrade your skills even more. The satisfaction from having a project accepted is comparable only to that from being able to apply the freshly learned skills straightaway to my work.

One important component is the support: 24/7 technical support, tutors answering your questions on Slack, weekly webinars, community managers who are constantly checking in with you to hear whether you are experiencing any issues - you receive support from everywhere, even grader pop up messages are insightful and funny! All in all it makes this journey so comfortable, even that the course is quite a commitment and you have to be ready for late nights and busy weekends)

I’m not new to Yandex Practicum. I tried their Interface Design program a few years ago, but although I didn’t finish it (it wasn’t my thing after all), I really liked the program itself, so I knew that I would come back.

How did I find myself in DataScience?

I changed jobs a year ago, and my new duties included working with spread sheets. I found working with data and formulas exciting, so I started looking for ways to implement this passion. I had heard of data science before, and it sounded too foggy and abstract to me. But at some point (after some research and a few videos on YouTube), I realised that it’s not that complicated, and, more importantly, it is exactly what I would like to do. So I started the DS training program, bearing in mind the thought that it will be just for fun. I said to myself that it would be a good way to spend my free time, a hobby with the potential to become something bigger.

How is it going?

I am in it for six months now, and I cam already say that there is no way back. The further I get — the more interesting it becomes. At the moment I am far more comfortable with Python and Pandas than with my old friends Excel and Google Sheets. I also really like how Yandex has built its learning environment. It feels like I am back at university, but now it is online, and it is also better. After completing the curriculum I am already aiming to take their course on mathematics (for now this one is only available in Russia), because I always wanted to be proficient in this domain. I didn’t see the way I could to this before, but now I believe that it is completely possible.

What’s so special about Practicum?

I feel like they did a really good job in gathering all the best learning tools and cutting off all the unnecessary elements of classic education. In our study process we have:

1. The very well written learning text. It is story-like theoretical material that comes in chunks. These chunks are split by interactive illustrations or graphs and short tasks in which you implement what you just learned. This way, you rarely get bored or unfocused, even with tough topics such as statistics. The platform also has a great coding environment, so you can work on your local machine, or completely in the web—whatever you choose.
2. Code review is the second one of the best things about this course. Each sprint ends with the course project; each project represents a possible business case (some of which I already encountered in my current job). My code is reviewed by real professionals of the industry. In their comments, they often leave very insightful advice, share tricks, and provide additional materials. Now I love when my work gets commented on.
3. Workshops and tutors. In addition to the main material, each week or two there is a workshop. It is like a web seminar, during which one of the tutors shows you how he approaches one of the cases on the topic. This happens online, so you can ask questions right during the process, but each workshop gets recorded so you can watch it later. I personally prefer to watch it later, following and repeating each step on my machine. You can also watch several records on the same topic, but with different tutors. Each of them has his or her own techniques and tricks, so it is also helpful.
4. Communications via Slack is a key part of the university-like experience. I can always ask questions or help others in public channels or in private conversations. I also get to share my thoughts, feelings, and achievements with other students from different cohorts. The community manager from my cohort writes to me from time to time, asking how I’m doing, whether I need help, and so on.

Phew. That’s a lot. In the end, I want to say that I wish I had had a school and university experience like this earlier, but I am grateful that I have it now. Of course, there are some places where Practicum could be improved, but i find them to be minor and not worth mentioning, and I know that the team is working on it. I also participated in a new design and features test for the platform. For that I was given with Amazon gift card, which I spend on buying books on machine learning and statistics.

You can reach me via LinkedIn or Telegram and ask questions if you want: search for Wanomir✌️.
And no, I wasn't paid for this 🙃