The statistical analysis for data science diploma typically covers the fundamental statistical concepts and methods that are essential for analyzing and interpreting data. The course covers topics such as probability theory, statistical inference, hypothesis testing, regression analysis, analysis of variance, and time series analysis. It also covers the application of statistical methods in data science, including data pre-processing, exploratory data analysis, data visualization, and data mining.
Professional Diploma in Statistical Analysis
for Data Science is a skill development programme offered by Pedagog, approved and
awarded by European International
University-Paris.
The course is geared towards students with a
basic understanding of statistics and programming and will prepare students for
more advanced courses in data science, machine learning, and artificial
intelligence.
This course is an ideal investment if you
want to nurture a career as a data analyst, data scientist, database
administrator, business intelligence analyst, and software developer in a wide
range of industries, including finance, healthcare, technology, and government
nationally & internationally.
The students are required to submit the
assignment in the form of a Performance-Based Task. This is a high-level
application-oriented end-of-the-course assessment that requires students to
create something out of what they have learned throughout the course.
On successful completion of the course, the
student will be awarded an Internationally accredited
Diploma Certificate from EIU-PARIS,
evidencing your competitive advantage locally and Internationally.
THE DUAL CERTIFICATE is awarded by
EIU-Paris (University) and Pedagog
Please Note: A Hard Copy of the certificate from the
university can be requested at an additional minimal fee, via e-mail
to hello@pedagog.ac
Upon completion of the course, graduates can pursue careers as data analysts, data scientists, database administrators, business intelligence analysts, and software developers in a wide range of industries, including finance, healthcare, technology, and government.
KM
Kumar Mangalam
09:00:00 PM 2024-01-01
Well organized learning workflow. I can see they put a lot of effort into this course, So far the course is going well. I pursued this course as I am aiming to work as a Data Scientist in various MNCs across the world and I can feel that this course would be able to make me achieve my dream.
European International University - Paris
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