Data Science with Python


The Data Science with Python certification course gives a complete overview of Python’s Data Analytics tools and techniques. Python is a major skill for many Data Science roles. Gaining knowledge in Python will be a means to unlock your career as a Data Scientist. Python is open source, interpreted, high level language and offers a great approach for object-oriented programming. It is one of the finest languages used by data scientists for various data science projects/applications. It lays out great study to deal with data science applications.

The three best and most significant Python collections for data science are NumPy, Pandas, and Matplotlib. … Matplotlib — A visualization collection that makes it quick and easy to generate charts from your data.  The most general library for machine learning work in Python.

 Python is one of the finest places to start your journey. This course focuses on how to get started with Python for data science course and by the end you should be comfortable with the basic concepts of the language.

Data science can be well-defined as a combination of mathematics, business acumen, tools, algorithms and machine learning techniques, all of which help us in finding out the hidden insights or patterns from raw data which can be of major use in the formation of big business decisions.

Python Course In Jaipur

1 Applied Plotting, Charting & Data Representation in Python 

The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures interpret into in terms of visualizations. The second week will concentrate on the know-how used to make visualizations in python and introduce users to finest practices when creating basic charts and how to realize design decisions in the context.

2 Applied Machine Learning in Python

The issue of dimensionality of data will be conferred, and the task of gathering data, as well as assessing those clusters, will be undertaken. Supervised tactics for creating predictive models will be described, and learners will be able to apply the scikit learn analytical modelling methods while understanding course issues related to data generalizability The course will end with a look at more advanced procedures, such as building groups, and practical limitations of predictive models.

3 Applied Text Mining in Python

The second week focuses on mutual manipulation needs, including regular expressions cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and determine how text classification is accomplished. The final week will sightsee more advanced methods for detecting the topics in documents and grouping them by similarity.

4 Applied Social Network Analysis in Python

The course begins with an understanding of what network analysis is and incentives for why we might model phenomena as networks. The second week introduces the concept of connectivity and network strength. The third week will explore ways of measuring the importance or centrality of a node in a network. The final week will explore the progress of networks over time and cover models of network generation and the link calculation problem.

data science course in jaipur

Data Science Course In Jaipur


  • Descriptive statistics
  • Understanding distributions and plots
  • Univariate statistical plots and usage
  • Bivariate and multivariate statistics
  • Intro to python
  • Variables
  • operators
  • datatypes and strings in python
  • Tuples
  • list
  • dictionary and set in python
  • Python functions and classes
  • Intro to numpy array
  • Intro to linear regression
  • Relationship between independent variable and target variable
  • Coefficient of correlation
  • Linear regression assumptions
  • Introduction to logistic regression
  • Sigmoid curve and logloss function
  • Model cases of logistic regression



 Python sanctions quick improvement and can associate with high-performance algorithms written in Fortran or C. IT also uses this in data mining, web development, scientific computing, and more. To put it simply, the demand for specialists with Python skills is on the leap. Python is a well-established language, used by data scientists and developers, which makes it easy to conspire across your institution through its simple syntax.

People choose to use Python so that they can communicate with other people. The other reason is established in academic research and statistical models. Python alone is adequate to apply data science in some cases, regrettably in the big businesses, it is just a piece of the puzzle for businesses to process their abundance of data. It’s feasible to work as a data scientist using either Python or R. Each language has its strengths and weaknesses, and both are entrenched in the industry.

Python is more inclusive, but R dominates in some industries. Plus, there are some admiring technical skills that suggest you learn along the way. Learn Python Fundamentals. Practice Mini Python Projects. Learn Python Data Science Libraries. Create a Data Science Portfolio as you grasp Python. Apply Advanced Data Science Techniques.



  • Data analysis techniques – Be Able to Read in Data from Different Sources & Clean the Data
  • Data analytics – Carry Out Data Exploratory & Pre-processing Tasks Such as Tabulation, Pivoting & Data Summarizing in Python
  • Become Proficient in Working with Real Life Data Collected from Different Sources
  • Carry Out Data Visualization & Understand Which Techniques to Apply When
  • Carry Out the Most Common Statistical Data Analysis Techniques in Python Including T-Tests & Linear Regression
  • Understand The Difference Between Machine Learning & Statistical Data Analysis
  • Implement Different Unsupervised Learning Techniques on Real Life Data
  • Implement Supervised Learning Techniques on Real Data
  • Evaluate The Accuracy & Generality of Machine Learning Models
  • Build Basic Neural Networks & Deep Learning Algorithms
  • Use The Powerful H2o Framework for Implementing Deep Neural Networks.



Data science with python course has appeared as an appealing career option for freshers as well as skilled professionals. The demand for data engineers is very high in sectors like information technology, telecom, manufacturing, finance and insurance, retail and many more. Entry-level data scientist salaries are as prompt as the job itself. If you can shatter the Amazon data science internship or Google data science internship, the experience you will gather here will give an edge to your career, and then there would be no retrospect. Paathfind gives you best python training in jaipur  and also best data science institute in jaipur which prepare you efficient Data Science Training by professionals.


In Conclusion, After learning Data Science with Python you will learn what data science is, why it is important, and the different libraries involved in data science. You will grasp the different skills needed when it comes to data science, such as exploratory data analysis, data wrangling, and model building.

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