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Enrich Data Science, ML and Analytics with powerful Visualisations using Matplotlib, Seaborn and Bokeh
Updated on Sep, 2026
Programming, Data Science, Data Analysis
Duration - 6.5 hours
Training 5 or more people ?
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If you are working on Data Science projects and want to create powerful Visualization and Insights as outcome from your projects, this course is for you!!!
If you are working on Machine Learning Projects and want to find patterns and insights from your Data on your way to building Models, this course is for you!!!
If you are a Business Analyst or Functional Analyst and want to build powerful Visualizations for your stakeholders, this course is for you!!
This course is exclusively focused on explaining how to build fantastic Visualizations using Python. Covers more than 20 types of Visualizations using the most popular Python Visualization Libraries Matplotlib, Seaborn and Bokeh. It covers Data Analytics that leads to building these visualizations so that the learners understand the flow of analysis to insights.
This course takes a holistic approach towards teaching Visualizations:
- Take real-life, business scenarios and raw data to go through detailed Exploratory Data Analysis (EDA) techniques to prepare your raw data to suit the appropriate Visualization needs.
- Data Analytics and Exploratory Data Analysis Techniques using multiple different data structures using Numpy and Pandas libraries.
- Explain Chart/Graph types, customization/configuration and vectorization techniques.
- Throughout the course, extensive amount of Code demo along with concepts as a balanced approach to teaching.
- Every concept is taught by going deeper into foundational techniques and deeper customizations on Visualizations.
Extensive Quizzes are infused at logical points to validate the learning effectiveness.
In-depth coverage of Matplotlib, Seaborn, and Bokeh Visualization Libraries.
Easy, step-by-step explanations with code to draw over 20 different kinds of charts and graphs using Python.
Extensive amount of Python - Matplotlib/Seaborn/Bokeh code used in the course is attached as downloadable resources for you to try out while you learn.
Use of Data Analytics Techniques / Exploratory Data Analysis (EDA) using several Data Generation and Manipulation Methods.
Extensive coverage of NumPy and Pandas Data capabilities using Python.
Learn the art of presenting Data in the form of Powerful, Innovative and Intuitive Visualisations that your stakeholders will love.
Application of Business and real-life Scenarios to create Visualisations.
Basic understanding of Python will be helpful, however not mandatory.
Check out the detailed breakdown of what’s inside the course
Hi there, I am Manas Dasgupta, from Bangalore, the Silicon Valley of India.
By qualification, I hold a Master's Degree (MSc) in AI from the Liverpool John Moores University (LJMU), UK.
My expertise area encompass Generative AI - RAG Application Development using Frameworks like LangChain and LlamaIndex, Machine Learning and Data Science / Predictive Analytics areas including various Supervised, Unsupervised, Deep Neural Networks, Clustering Techniques, etc.
My research areas in Masters were Natural Language Processing (NLP) using Deep Learning Methods such as Siamese Networks, Encoder-Decoder techniques, various Language Embedding methods such as BERT, areas such as Supervised Learning on Semantic Similarity and so on.
I have > 20 Years of experience in the IT Development mostly in the Financial Services domain, developing products and solutions. I am also the Founder of Teksands where me and my team develop Gen AI rich applications in the Talent space.
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