Breaking Down the LearnBay Data Science Curriculum: What You Will Learn (1)

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Breaking Down the LearnBay Data Science
Curriculum What You Will Learn
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The constant changes in the environment present a
significant concern for data science students,
due to which a balanced education is essential to
thrive in this field. The details of the data
science course in Jaipur in LearnBay are laid
down so that students get adequate knowledge and
skills in this competitive sector. Below are
details of the LearnBay data science course and
what the learners stand to learn in each
programs phases.   
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1. Starting the course Data Science and
Analytics    Overview of Data Science    Starting
from the definition of data science, its
significance, and examples of its use, the course
also describes the principal duties of a data
scientist. It covers stages of the data science
cycle data gathering and acquisition,
pre-processing, data processing, and data
presentation.    Basic Concepts and Tools    Here
you will be acquainted with what data science is
and the key ideas as well as the tools applied in
the course of its practice. This entails a brief
introduction to Python, R, and SQL as these are
the main programming languages that are used in
data science. You will also learn about Jupyter
Notebooks which is an IDE for programming in
Python and RStudio which IDE is for using R. 
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2. Statistics and Probability    Descriptive
Statistics    Descriptive statistics is among the
areas covered in the curriculum this focuses on
techniques of summarizing and describing the main
characteristics of a given data set. You will
discover how measures of central tendency work,
including mean, median, and mode, or measures of
dispersion that include range, variance, and
standard deviation.   
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3. Data Manipulation and Cleaning    Data
Wrangling  Data cleaning focuses on getting
the data in a suitable format for research and
analysis. This will include dealing with cases of
missing data, managing extreme values, and
managing records that may be duplicated. This is
an essential phase of the data analysis since it
enhances the quality of the data collected and
used in the study.   
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3. Data Manipulation and Cleaning    Data
Wrangling  Data cleaning focuses on getting
the data in a suitable format for research and
analysis. This will include dealing with cases of
missing data, managing extreme values, and
managing records that may be duplicated. This is
an essential phase of the data analysis since it
enhances the quality of the data collected and
used in the study.   
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4. Data Visualization    Dashboarding and
Reporting    You will also discover ways to
construct active dashboards and reports using
tools like Tableau and Power BI. These tools
assist you in ensuring that your findings are
well presented so that the stakeholders can be in
a better position to implement the recommended
solutions. 
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5. Machine Learning    Supervised
Learning    Supervised learning requires the use
of trained data. The types of supervised learning
algorithms you will be introduced to include
linear regression, logistic regression, decision
trees, and support vector machines (SVM). Other
concepts that will be covered include the ideas
of cross-validation and confusion matrices used
in evaluating models.    Unsupervised
Learning    Unsupervised learning works and
deals with data that have no labels or targets to
predict attached to them. You will learn about
clustering algorithms such as the k- k-means and
hierarchical clustering and dimensionality
reduction methods such as PCA.     
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Conclusion    The data science course in Jaipur
successfully delivered by LearnBay includes all
that you need for a good start in the world of
data science. This course includes all the topics
in data science, from basic concepts to advanced
methods and big data. LearnBay also guarantees
you practical experience and real project
completion to meet the needs of the modern
data-driven world.