The use of content of this portal is governed by the following terms and conditions:
A. The Intended Audience/ Target for the Portal
- This portal is designed for individuals registered for various Big Data/ Data Science training and certification programs of partners of the Data Science Skool.
- The content appearing here has been written to assist, supplement and complement learning through providing examples, programming tests, practice problems, design situations and cases related to all aspects and topics generally covered in global training and certification programs offered by leading international institutions and certifications including DASCA:
- Big Data Analysts
- Big Data Engineers and application developers
- Data Scientists and Data Leaders
B. The Nature of Content on the Portal
- The contents of this portal neither purport to, nor are meant to work as a complete text-portal/ website-type reference resource for users.
- The language, style, and nature of content on this portal has been designed keeping in view the global standards of English fluency.
- The course-writers contributing to this portal have assumed that the user/ learner at least has a basic level understanding of the principles and concepts that a Bachelor's/ Undergraduate Degree holder in Data Systems/ Information Technology/ Business Management/ Statistics/ Software Programming or Computer Science from a university generally is expected to have.
- Those not belonging to Data Science and Big Data fields will have to take a pre-course in these topics to be able to fully use content on this portal, and hence, The Data Science Skool does not take any responsibility for -, or make any such claim – about the use, effectiveness, or comprehensibility of content presented here being equal for all types of users.
- Further, it should be noted that all learners and users who exhibit practical exposure to basic functions and tasks of Data Science and Big Data, and are aware about the general global trends in these fields are more likely to leverage this portal better for more complete and expanded learning.
- The best use of content on this portal is made by learners who have knowledge of the state-of-the-art principles, theories, techniques, tools and generally accepted practices of Data Science and Big Data.
- Without exception, all Data Science and Big Data learners using this portal are expected to not only exhibit reasonably high levels of proficiency in comprehending standard written English, but also a decent exposure to the generally accepted principles and norms of Data Science and Big Data practice.
C. The Coverage and Focus of the Portal
- A majority of this content has been researched and prepared by independent data science experts with the objective of providing support to learning in data science.
- Hundreds of technology experts, senior recruiters, evangelists, platform developers, and Big Data professionals working for leading global Big Data solution providers across the world have contributed to the content appearing on this portal.
- Structurally, this portal contains content to support around 30 core knowledge topics.
- This portal intends to provide a reliable research–backed presentation of learning content in performance–critical knowledge areas in the four most important professional practice vectors in Big Data – Big Data Analytics, Big Data Engineering, and Data Science.
- The Data Science Skool approach toward Data Science and Big Data learning is entirely guided by an informed belief, that professionals need to rise above technologies and platforms, and develop generic skills in Data Science and Big Data, if they really want to have a longer shelf life as Data Science professionals.
D. The Redundancy of Content on the Portal
- The Data Science Skool makes all attempts to keep content updated to the latest in the field of Data Science.
- Big Data is expanding fast and furious, and hence, it is impossible for The Data Science Skool to assure or claim that the content appearing on this portal completely covers all aspects and dimensions of Data Science or Big Data theory, practice, or philosophy at all times.
E. Linkages with Exams
- The contents on this portal neither purport to, nor are designed for exam purposes. This portal does not claim to assist any user/ learner in the preparation of any certification or academic exam.
- Users of this portals should be careful and not assume, that the practice questions, exercises, or problems presented on this portal are linked to any specific exams.
F. Limits of Liability
- While the best of efforts, research and rigor have been invested in the preparation of this portal, the contributors make no representation or warranties with respect to the accuracy or completeness of the same; and speciﬁcally disclaim any implied warranties of merchantability or ﬁtness for any - particular purpose.
- There are no warranties which extend beyond the descriptions contained in this clause.
- No warranty may be created or extended by sales representatives in written or online sales materials.
- The accuracy and completeness of the information provided herein and the opinions stated herein are not guaranteed or warranted to produce any particular results, and the advice and strategies contained herein may not be suitable for every individual.
- The contributors shall not be liable for any loss of proﬁt or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.