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The entire training includes real-world projects and highly valuable case studies.
IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.
Statistics is one of the core disciplines of Data Science. Statistics is a vast field of study and Data Science requires only certain knowledge areas from Statistics such as data harnessing from various sources, understanding types of data and mathematical operations than can be performed on it, exploratory data analysis, measures of central tendencies and variability, hypothesis testing etc. As Data Science is about deriving insights from Data, Statistics becomes an important knowledge area.
Statistics as a field is vast and requires significant time and effort to gain practitioner level knowledge. This course is specifically designed to impart required statistics knowledge for data science practitioners. The syllabus of the course is in line with the international curriculum including knowledge areas of statistics that are quintessential for data science.
Statistics for the Data Science course take a practical approach by applying statistics concepts through case studies in the python platform, thereby enabling the candidates to learn essential statistics in the shortest and efficient way.
DataMites has provided training over 10,000 candidates in Data science courses across the globe and recognized as a leading institute for Data Science courses.
Statistics for Data Science course is designed as per the guidelines of the International Association of Business Analytics Certifications, IABAC.org a global board based in the Netherlands.
IABAC® standards are aligned with the European Council and, thereby providing a strong basis for course coverage and quality of the training.
The trainers of DataMites™ are Ph.D. scholars with more than 15 years of Analytics industry experience.
In short DataMites™ provides high-quality course training with practical case study approach, aligned with global standards.
Data Science involves extracting valuable insights from large datasets, both structured and unstructured, by identifying hidden patterns and trends.
Learning Data Science offers numerous benefits, including improved customer experience, increased job opportunities, higher salaries for Data Science professionals, access to various job titles, and involvement in company decision-making processes.
Data Science Certification courses are open to anyone interested in learning, regardless of their background. Engineers, marketing professionals, software and IT professionals, and even newcomers can participate in part-time or external Data Science programs. Basic high school level subjects are usually the minimum requirement for regular Data Science courses.
The Data Science Training Fee varies depending on the level of training. However, the typical range for classroom training in Data Science is between 1000 USD to 3000 USD.
After completing Data Science training, individuals can pursue various job roles, such as Data Scientist, Machine Learning Engineer, Machine Learning Scientist, Application Architect, Data Architect, Data Engineer, Statistician, Data Analyst, Business Intelligence Analyst, and Marketing Analyst.
Technical skills like data analysis, statistical knowledge, data storytelling, communication, and problem-solving are advantageous for learning Data Science.
The duration of a Data Science course can range from 2 months to 1 year, depending on the subject level and syllabus designed for different branches within Data Science.
While having a strong programming background, including knowledge of Python, R, Excel, C++, Java, and SQL, is preferred, it is possible to learn programming from the basics and improve gradually.
Like any other field, with proper guidance, Data Science can be easy to learn and build a career in. However, due to its vastness, beginners may find it challenging and frustrating without proper direction and support.
Major tools used in Data Science include SAS, Apache Hadoop, Tableau, BigML, Knime, RapidMiner, Excel, Apache Flink, and Power BI.
Data Science has a wide scope as it enables companies to efficiently analyze and derive valuable insights from massive amounts of data. It is extensively used in various industry domains such as marketing, healthcare, finance, banking, and policy work, among others.
Most entry-level analytics jobs in India do not require specialization or post-graduation. Companies primarily look for aptitude, communication skills, and critical reasoning, making it possible for freshers to pursue Data Science courses and secure employment.
Yes, it is possible to transition from a mechanical background to a career in Data Science. Although a mechanical engineering background may not directly align with Data Science, it provides a strong foundation in mathematics, problem-solving skills, and analytical thinking, which are valuable in the field.
Yes, it is possible to transition from a non-coding background to a Data Science background. While prior coding experience can be beneficial, it is not a strict requirement for entering the field. Many individuals with non-coding backgrounds have successfully switched to Data Science roles.
DataMites™ provides flexible learning options from traditional classroom training, lastest virtual live classroom to distance course. Based on your location preference, you may have one or more learning options.
This course is perfectly aligned to the current industry requirements and gives exposure to all latest techniques and tools. The course curriculum is designed by specialists in this field and monitored and improved by industry practitioners on continual basis.
All certificates can be validated with your unique certification number at IABAC.org portal. You also get candidate login at exam.iabac.org, where you can find your test results and other relevant validation details.
The results of the exam would be reflected immediately when you take the test online at exam.iabac.org portal. The certificate issuance, as per IABAC™ terms, takes about 7-10 business days for e-certificate.
No, the examination fees is already included in the course fee and you would not be charged any extra.
Course fee needs to be paid in one payment as it is required to block your seat for the entire course as well as book the certification exams with IABAC™. In case, if you have any specific constraints, your relationship manager at DataMites™ shall assist you with part payment agreements.
DataMites™ has a dedicated Placement Assistance Team(PAT), who work with candidates on individual basis in assisting for right Data Science job.
You get 100% refund if you are not satisfied with the training but the exam cannot be refunded as we pay to accreditation bodies. If the refund is due to your availability concerns, you may need to talk to the relationship manager and will be sorted out on case to case basis.
DataMites™ provides loads of study materials, cheat sheets, data sets, videos so that you can learn and practice extensively. Along with study materials, you will get materials on job interviews, new letters with latest information on Data Science as well as job updates.
Statistics is crucial because it helps in collecting data, choosing the right analysis methods, and effectively presenting results. It plays a vital role in making discoveries in science, making data-driven decisions, and making predictions.
Statistics is a discipline rooted in mathematics that primarily deals with the collection and analysis of quantitative data. On the contrary, data science is a multidisciplinary field that employs scientific techniques to extract insights and knowledge from data in diverse formats.
The Statistics for Data Science Training covers essential areas of statistics that are relevant to data science, such as data collection, understanding different types of data, mathematical operations on data, exploratory data analysis, measures of central tendencies and variability, and hypothesis testing. It provides the necessary statistical knowledge required for deriving insights from data in the field of data science.
There are no strict prerequisites for the Statistics for Data Science Courses, but basic mathematics skills are recommended. Basic programming skills can also be beneficial for Python case studies.
The Statistics for Data Science Course is suitable for freshers, individuals aspiring to build a career in machine learning and data science, professional data scientists, managers, and business analysts who want to enhance their analytical skills through statistical methodologies.
By completing the Statistics for Data Science Course, candidates can gain effective statistical skills and a practical understanding of applying these techniques to various data problems in different areas. The course provides a practical approach to learning statistics for data science.
DataMites is a globally accredited institute for Data Science, recognized by the International Association of Business Analytics Certifications (IABAC). With over 25,000 enrolled students, DataMites offers a three-phase learning approach, including self-study materials, intensive live online training, and real-world projects and case studies. After completing the training, candidates receive the IABAC Statistics for Data Science Certification, which holds global recognition. DataMites also provides internship opportunities with Rubixe, a global technology company.
The fee for the Statistics for Data Science Course at DataMites is as follows:
The DataMites Statistics for Data Science Program has a duration of 6 months.
While DataMites offers classroom training exclusively in Bangalore at present, we are open to arranging classroom training in other locations upon request. The availability of such training depends on the demand and the presence of other candidates from the specific location.
DataMites ensures that the trainers are certified and highly qualified, with decades of experience in the industry and expertise in the subject matter.
The FLEXI-PASS allows candidates to attend DataMites sessions for a period of 3 months, providing flexibility for clearing queries or revising topics.
Yes, DataMites will issue the IABAC® certification, which provides global recognition of the acquired skills.
Yes, upon completing the course, DataMites will issue a course completion certificate.
Yes, you need to carry a photo ID proof such as a national ID card or driving license for issuing a participation certificate and booking certification exams if required.
If you miss a session, you can contact your trainers to schedule a makeup class according to your availability. For online training, every session is recorded and uploaded, allowing you to catch up at your own pace.
Yes, DataMites provides a free demo class to give you an overview of the training and the topics covered.
Yes, DataMites has a dedicated Placement Assistance Team (PAT) that provides placement support after completing the course.
DataMites follows a case study approach to learning, which includes theory, hands-on practice, case studies, project work, and model deployment.
Yes, you can request support sessions to clarify any topics or concepts that you need a better understanding of.
DataMites accepts various modes of payment, including cash, net banking, cheque, debit card, credit card, PayPal, Visa, MasterCard, and American Express.
The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -
The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.
No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.
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