A data science course is an educational program or series of classes that teaches individuals the skills, techniques, and tools needed to work with data effectively.
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Eligibility to pursue data science course
Educational Background:
Undergraduate Level: Many data science courses, especially bachelor's or diploma programs, may
require a high school diploma or its equivalent as the minimum educational background.
Graduate Level: For master's or postgraduate data science programs, a relevant bachelor's degree
is typically required. This degree may be in fields such as computer science, mathematics,
statistics, engineering, or a related discipline. Some programs may also consider applicants with
degrees in non-technical fields but may require prerequisite coursework.
Prerequisite Knowledge:
Some data science programs expect students to have a basic understanding of mathematics and
statistics. Proficiency in programming languages like Python and R may also be required or
recommended.
Standardized Tests:
Some institutions may require standardized test scores like the GRE (Graduate Record
Examination) for admission to graduate-level data science programs. Be sure to check the specific
requirements of the institution you're interested in.
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JobOpportunitiesinDataScience
Data Scientist: Data scientists are responsible for collecting, processing, and
analyzing large datasets to extract valuable insights and make data-driven
decisions. They often use machine learning and statistical techniques to build
predictive models.
Data Analyst: Data analysts focus on analyzing data to provide actionable
insights for businesses. They use tools and techniques to clean and visualize
data, identify trends, and create reports to support decision-making.
Machine Learning Engineer: Machine learning engineers develop and
implement machine learning models and algorithms. They work on building
and deploying predictive models for tasks like recommendation systems,
image recognition, and natural language processing.
4. Programming Languages used in Data Science
Course
Python: Python is one of the most popular programming languages for data science
due to its simplicity, extensive libraries, and community support. Libraries like
NumPy, pandas, Matplotlib, and scikit-learn are commonly used for data
manipulation, analysis, and machine learning.
R: R is a language designed for statistical analysis and data visualization. It is often
used in data science courses, especially those with a strong focus on statistics and data
visualization. Packages like ggplot2 and dplyr are popular in R for data manipulation
and visualization.
SQL (Structured Query Language): SQL is essential for working with relational
databases, which are commonly used in data analysis. Data science courses often
cover SQL for data retrieval and manipulation.
5. Tools Used in Data Science course
Jupyter Notebooks: Jupyter is an open-source web
application that allows for interactive coding and data
visualization. It's widely used for data exploration,
analysis, and sharing code and results.
RStudio: RStudio is an integrated development
environment (IDE) specifically designed for the R
programming language. It's a popular choice for
courses that focus on R-based data analysis.
Python IDEs: Depending on the course, various Python
IDEs (Integrated Development Environments) may be
used, including PyCharm, Visual Studio Code, and
Spyder, among others.
6. Upcoming Batches in Delhi
• Training Dates:
– 2nd October 2023 (Weekday – Online )
– 9th October 2023 (Weekday – Online)
– 14th October 2023 (Weekend – Online)
– 16th October 2023 ( Weekday – Online)
– 16th October 2023 ( Weekday – Classroom)
– 21st October 2023 (Weekend – Classroom)
– 23rd October 2023 ( Weekday – Classroom)
– 28th October 2023 ( Weekend – Online)
– 30th October 2023 (Weekday – Online)
• Classroom Training in Bangalore, Chennai, Pune, and Hyderabad
Course Details
• 8 Months Course
• 4 Months of Classroom Training
• 4 Month Project work
• IABAC Certification
• Internship Project
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