
Databricks Certified Machine Learning Associate - Mock Exams
Description
Databricks Certified Machine Learning Associate
This course is designed to thoroughly prepare you for the official Databricks Machine Learning Associate certification. It offers six comprehensive mock exams, each carefully crafted to simulate the actual certification exam experience. These exams not only test your knowledge of Databricks and machine learning concepts but also provide detailed explanations for each answer, ensuring you fully understand the material.
Throughout the course, you will encounter a wide range of questions that cover the critical topics needed for the certification, including data preparation, feature engineering, model selection, evaluation, and deployment within the Databricks platform. Whether you're experienced with Databricks or looking to solidify your foundational knowledge, this course will guide you through key machine learning principles while helping you become proficient with Databricks tools and services.
By completing the six mock exams and reviewing the explanations for correct and incorrect answers, you'll strengthen your understanding of both the subject matter and the nuances of how Databricks handles machine learning workflows. This course is an ideal resource for anyone aiming to pass the Databricks Certified Machine Learning Associate exam with confidence and deepen their expertise in data science and machine learning.
Can I retake the practice tests?
Yes, you can attempt each practice test as many times as you like. After completing a test, you'll see your final score. Each time you retake the test, the questions and answer choices will be shuffled for a fresh experience.
Is there a time limit for the practice tests?
Yes, each test includes a time limit of 120 seconds per question.
What score do I need to pass?
You need to score at least 70% on each practice test to pass.
Are explanations provided for the questions?
Yes, every question comes with a detailed explanation.
Can I review my answers after the test?
Absolutely. You’ll be able to review all your submitted answers and see which ones were correct or incorrect.
Are the questions updated frequently?
Yes, the questions are regularly updated to provide the best and most relevant learning experience.
Additional Note: It’s highly recommended that you take the practice exams multiple times until you're consistently scoring 90% or higher. Don’t hesitate—start your preparation today. Good luck!
Who this course is for:
- Data Scientists and Machine Learning Engineers
- Data Analysts and Data Engineers
- AI and ML Enthusiasts
- Students and Recent Graduates
- Technical Consultants and Solution Architects
- Business Intelligence and Analytics Professionals
- Professionals Pursuing Advanced Databricks Certifications
Instructor
EN
Python Developer/AI Enthusiast/Data Scientist/Stockbroker
Enthusiast of new technologies, particularly in the areas of artificial intelligence, the Python language, big data and cloud solutions. Graduate of postgraduate studies at the Polish-Japanese Academy of Information Technology in the field of Computer Science and Big Data specialization. Master's degree graduate in Financial and Actuarial Mathematics at the Faculty of Mathematics and Computer Science at the University of Lodz. Former PhD student at the faculty of mathematics. Since 2015, a licensed Securities Broker with the right to provide investment advisory services (license number 3073). Lecturer at the GPW Foundation, conducting training for investors in the field of technical analysis, behavioral finance, and principles of managing a portfolio of financial instruments.
Founder at e-smartdata
PL
Data Scientist, Securities Broker
Jestem miłośnikiem nowych technologii, szczególnie w obszarze sztucznej inteligencji, języka Python big data oraz rozwiązań chmurowych. Posiadam stopień absolwenta podyplomowych studiów na kierunku Informatyka, specjalizacja Big Data w Polsko-Japońskiej Akademii Technik Komputerowych oraz magistra z Matematyki Finansowej i Aktuarialnej na wydziale Matematyki i Informatyki Uniwersytetu Łódzkiego. Od 2015 roku posiadam licencję Maklera Papierów Wartościowych z uprawnieniami do czynności doradztwa inwestycyjnego (nr 3073). Jestem również wykładowcą w Fundacji GPW prowadzącym szkolenia dla inwestorów z zakresu analizy technicznej, finansów behawioralnych i zasad zarządzania portfelem instrumentów finansowych. Mam doświadczenie w prowadzeniu zajęć dydaktycznych na wyższej uczelni z przedmiotów związanych z rachunkiem prawdopodobieństwa i statystyką. Moje główne obszary zainteresowań to język Python, sztuczna inteligencja, web development oraz rynki finansowe.
Założyciel platformy e-smartdata