An Introduction to Data Science

Visualize and Play with data, try to handle data efficiently..
Free tutorial
Rating: 3.4 out of 5 (260 ratings)
10,494 students
44min of on-demand video
English [Auto]

Data Science and its History
Road map or procedure to master data science and become a data scientist.
It’s requirements and application in various fields
Difference Between Noise and Real Data
How to become expert in data science .
what are the skills required to be data scientist.


  • no prior knowledge about Data Science is required
  • willingness to learn new


# This course focuses on the  fundamental aspects Data Science.

Which is developing  field  &  also the future of Artificial Intelligence.

you will also get to know :

# Basic concepts like noise vs data and different types of graphs to represent data.

# All you need to know to master data science and get your dream job.

# The course content is based on Research and its real.

# The upcoming courses will be based on relevant topics for which this will be prerequisite.

# So complete this course and stay connected to me to get info about upcoming courses.

& this will help you to boost up your career.....

Who this course is for:

  • Anyone who is curious about data science.
  • Students in field of data science.
  • Data experts to master their skills and become data scientist .
  • Anyone who is willing to learn can join.


Google Certified Python Expert | Google Chrome Extension Dev
Kumar Rajmani Bapat
  • 3.6 Instructor Rating
  • 911 Reviews
  • 66,091 Students
  • 9 Courses

Hello Everyone !!

I am a self-driven and motivated computer scientist with the ability to develop and maintain robust software products, web apps, and data science projects of almost any type. Having a specialization in the area of data science and software development with a core interest in AI and Cloud Technologies. I have hands-on experience in analyzing data using SQL and Python and Tableau, and Excel, also in applying machine learning algorithms to building high-accuracy models for prediction and developing large-scale software scalable applications, etc. I earlier worked as a Data Engineer Intern at Indian Meteorological Department for a year and where I worked on a live project and developed an AI-based Crop disease detection System with 92 percent accuracy. Furthermore, my major project was a B2B Ecommerce Website that was developed in Django, Flask and Java, SQLite, and Javascript. I also presented it at an International Conference and it was published in an international journal. I have completed training in the Google Cloud Platform by Google on Cloud Engineering and Data Science and Machine Learning Tracks and have good experience and understanding working with it also.

Programming Languages Expertise: Java, Python, C, C++, Assembly.

Global Certificates and Batches: Google Cloud Engineering and Machine Learning all tracks completed Batches, Microsoft Certifed Azure and Data Fundamental, DET.

Development tools: Django, Flask, Excel, Tableau, PostgreSQL Jupyter, Visual Studio Code, GCP, Hadoop, Spark, Windows/Linux, Office, and Python Libraries for Advance data analysis.

Apart from this, I am an Instructor of some amazing courses here at Udemy such as

Python for Data Science and Machine learning and Flask and Now coming the latest one etc.

I have also authored a few research-based books such as Predictive Data Analysis using python etc.

In my spare time, I like Playing Chess, Reading Articles, Coding, Solving Statistics, and data-related problems, and Learning new things. I have also won around 20+ trophies in Open Chess Tournaments till now.

I hope you like My Courses' Content and Exclusive Materials and Documentation feel free to provide your Good Rating and Feedback. And Stay Tuned and will continue bringing more such courses to stay productive and updated with the latest trends in Data Science and Machine Learning and Computer Science Engineering. If you want to contact me regarding anything you can reach me through LinkedIn or email or Messages section etc.

Thank you.

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