Certified Professional in Data Science - Practice Test
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📖About This Course
**Course Updated - September 2022**>> COURSE REGULARLY UPDATED: NEW TIPS, MORE LESSONS <<Data Science grew through our experiences with Business Intelligence BI, a field that became popular in the 1990s. However, the last 20 years have seen unprecedented improvement in our ability to take action using Artificial Intelligence. As we adopt the BI methodologies to AI deployments, how will these methodologies morph to add considerations needed for model deployment, and machine learning?Today’s Data Science work deals with big data. It introduces three major challenges:How to deal with large volumes of data. Data understanding and data preparation must deal with large-scale observations about the population. In the world of BI on small samples, the art of data science was to find averages and trends using a sample and then project it using universal population measures such as census to project to the overall population. Most of the big data provide significant samples where such a projection may not be needed. However, bias and outliers become the real issuesData is now available at high velocity. Using scoring engines, we can embed insights into high velocity. Data Science techniques offer significant real-time analytics techniques to make it possible. As you interact with a website or a product, the marketer or services teams can provide help to you as a user. This is due to insight embedded in high velocity.Most of the data is in speech, unstructured text, or videos. This is a high variety. How do we interpret an image of a driver's license and extract a driver's license? Understanding and interpreting such data is now a central part of data science.As these deployed models ingest learning in real-time and adjust their models, it is important to monitor their performance for biases and inaccuracies. We need measurement and monitoring that is no longer project-based one-time activity. It is continuous, automated, and closely monitored. The methodology must be extended to include continuous measurement and monitoring.What will you need to succeed in this Exam?Excel, Statistics and Python knowledge is required though - you don't need to be an expert but the basics need to be set (though there are refresher sections in this course!)NO Android, Java, Swift, or C knowledge is required!What does this course offer you?This course consists of 2 practice tests.The practice test consists of 20 questions, timed at 30 minutesThe questions are multiple-choice.Every question is associated with a knowledge areaThe answers are randomized every time you take a testOnce the test was taken, you will get an instant result report with categories of strength to weakness.You can retake the tests over and over again as and when it suits you.I'd be very happy to welcome you to the course!
Certified Professional in Data Science - Free Udemy Course [100% Off Coupon Code]
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What You'll Learn in This Free Udemy Course
This comprehensive free online course on Udemy covers everything you need to become proficient in data science exam preparation. Whether you're a beginner or looking to advance your skills, this free Udemy course with certificate provides hands-on training and practical knowledge you can apply immediately.
- Master 20-question practice tests to build confidence and exam readiness
- Analyze randomized multiple-choice questions across key data science knowledge areas
- Develop expertise in Excel, Statistics, and Python fundamentals required for certification
- Learn to interpret big data challenges including volume, velocity, and variety
- Understand modern data science methodologies beyond traditional Business Intelligence
- Gain insights into real-time analytics and high-velocity data processing
- Prepare for model deployment considerations in machine learning environments
- Build skills to identify and mitigate biases in deployed AI models
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Meet Your Instructor
Learn from MOHNAS LTD, an experienced professional in data science education. With thousands of satisfied students across their courses, this industry veteran brings proven track record in simplifying complex data concepts. Their teaching style focuses on practical application and real-world scenarios, making advanced topics accessible to learners at all levels.
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With an impressive 4.31 rating and 3,855 students already enrolled, this Udemy free course has proven its value. The course includes 1 comprehensive lesson, all taught in English. What sets this free online course apart is its focused exam preparation approach with instant feedback and category-based strength analysis. Upon completion, you'll receive a certificate to showcase on LinkedIn and your resume. Plus, with mobile access, you can learn anytime, anywhere—perfect for busy professionals. This IT & Software course in the IT Certifications niche is regularly updated and includes lifetime access, meaning you can revisit materials whenever you need a refresher.
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⚠️ Important: This free Udemy coupon code expires on October 31, 2025. The course will return to its regular $19.99 after this date, so enroll now while it's completely free. This is a legitimate, working coupon—no credit card required, no hidden fees, no trial periods. Once enrolled, the course is yours forever.
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Is this Udemy course really 100% free?
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How long do I have to enroll with the free coupon?
This limited-time offer expires on October 31, 2025. After this date, the course returns to its regular $19.99 price. We highly recommend enrolling immediately to secure your free access. The coupon has limited redemptions available.
Will I receive a certificate for this free Udemy course?
Absolutely! Upon completing all course requirements, you'll receive an official Udemy certificate of completion. This certificate can be downloaded, shared on LinkedIn, and added to your resume to showcase your new skills to employers.
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Frequently Asked Questions
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Upon completion of all video lectures, Udemy will issue a certificate of completion.
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Once you enroll with the coupon, you get full lifetime access to the materials.
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