[2026 Big Data Certification Practical Exam Preparation] 100% Pass the Big Data Analysis Engineer Practical Exam! See the Pattern in Past Questions!

This is an excellent course for intensive learning. I learned econometric analysis with Stata, so I started without knowing even the basics of Python. The biggest advantage is that the instructor answers questions in real-time. I barely passed after going through the course three times, and I think it would be an even better course if each problem were solved in 2-3 different ways!

I'm a non-major who passed the practical exam with a 90 and wanted to leave a review!! I knew statistics well but had absolutely no knowledge of coding, so I was at a loss. I watched the YouTube pandas lectures about 3 times and the Inflearn past exam lectures about 3 times too! I recommend copying and pasting the past exam code in the test environment and following along. Thank you for creating virtual data and sharing the code.. Both Inflearn and YouTube were incredibly helpful. Thank you for teaching so easily and well. I don't think I would have passed without this course... Your voice is also calm, so it really sticks in my ears. Oh, for this exam's Type 2 problem, I submitted without doing train test split and got an f1 score of 1.0, but 5 points were deducted😭😭 But when I did split, I got 0.5, so I couldn't submit that😭 It was probably data with a large imbalance.. I'll study hard based on the coding knowledge I learned! I recommend this course

Concise and good. Thanks to it, I passed the 10th exam!

No help from other courses, I passed 1st try with 90, only with this course.🖐 Excellent course for learning from basics to application. Thank you!!!

Best teacher, best class

It was so incredibly helpful. While working, finding past questions or mock exams was a struggle, and I was at a loss as to what to do, but they provided all the code and explained everything kindly, thanks to which I passed! ! It's the best!! Highly recommended!!

Today was the preliminary score announcement day, and I passed! I couldn't solve Type 3 at all due to insufficient study, and in Type 1 preprocessing, I only solved 2 problems, so I had to get a perfect score in Type 2, and fortunately I did, so I barely passed with 60 points. The advantage of this lecture is that it proceeds with learning based on actual past exam questions, making it easy to adapt to exam problems, and since the lectures aren't long, efficient learning is possible. The instructor also conducts the lectures smoothly without any hiccups, and especially answered questions very quickly. I also think it's a big advantage that the lectures aren't boring. However, regarding the encoding or scaling process of Type 2, I hope additional explanations (which encoding to apply in which situation, which scaler to apply to perform scaling, etc.) are added a little more. It felt a bit like I was just memorizing code..😊😊 Of course, even if you just memorize the code template, you can get a perfect score in Type 2. For this exam's Type 2 problem-solving, I used the 'one-hot encoding + RandomForestRegressor(Random_State set to 42 only)' template and got a perfect score! I didn't even do separate scaling. 코딩 대한민국's YouTube Preprocessing 100 Problems and this Inflearn paid lecture were really a great help. Thank you. * Since I barely passed and left a course review, for those who might be looking for 빅분기 practical lectures, I'm leaving an additional comment in case it influences your choice of lecture. I only barely passed because my study time was too short..😭😭 I'm also a beginner non-major😊😊 (Passed written exam on 2nd try, practical on 1st try!)

For those with Python experience, I think it's a straightforwardly good subject.