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# Introduction to Data Science (Handwritten) Study Notes PDF

Introduction to Data Science Tutorial and Handwritten Study Notes PDF

These Introduction to Data Science PDF Study notes & tutorials will help you to get conceptual deeply knowledge about it. We are here to provides you the Best tutorials, Study Notes and Lecture notes from best institutions like MIT (Open Course), IIT (NPTEL), Washington University, California University, University of Oxford, Cornell University, Stanford University etc… which could be help you to understand concepts to Ace in BCA, BSc, B.tech/B.E course and crack any kind of Competition exams Like etc... and Ace the data science interview pdf. The huge Benefit of these notes i.e. all tutorial, Handwritten & Digital Notes are Free.

In Data Science, data preprocessing involves preparing raw data for further analysis. It includes tasks such as data cleaning, data wrangling, data scaling, and data transformation. Let’s take a closer look at each of these topics

## Topics Covered in Data Science Tutorial & Study Notes PDF:

• Introduction to Data Science for beginners and advanced
• Basic Mathematics for Data Science (Linear functions, equations, regression, least square, graph theory, Linear Algebra, Matrices, Tensors etc..)
• Data Science / Data Analytics
• Data Mining
• Maching Learning
• Big Data
• Introduce R-Programming language for data science (Used for data analysis & manipulation)
• Packages (Data analysis, graphics, etc…)
• Data science and analytics
• Support-Graphics (only in this technology)
• Case-sentitive
• High-dimensional space and its properties
• Linear algebra and Singular Value Decomposition
• Spectral methods
• Random walks and their applications
• Random graphs and network models
• Algorithms for massive data sets and space-efficient data structures
• Convex optimisation
• Clustering
• mathematical foundations required for data science
• first level data science algorithms
• data analytics problem solving framework
• practical capstone case study Learning Outcomes etc…

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