Python Machine Learning with Data Analysis Data Science Course in Udaipur

  • Installation Setup and Overview

  • IDEs and Course Resources

  • iPython/Jupyter Notebook Overview

Learning Intro to numpy

  • Intro to numpy

  • Creating arrays

  • Using arrays and scalars

  • Indexing Arrays

  • Array Transposition

  • Universal Array Function

  • Array Processing

  • Array Input and Output

Pandas

  • Series

  • DataFrames

  • Index objects, Reindex

  • Drop Entry , Selecting Entries

  • Data Alignment

  • Rank and Sort

  • Summary Statistics

  • Missing Data

  • Index Hierarchy

Working with data

  • Reading and Writing Text Files

  • JSON with Python

  • HTML with Python

  • Microsoft Excel files with Python

  • Merge ,Merge on Index

  • Concatenate

  • Combining DataFrames

  • Reshaping Pivoting

  • Duplicates in DataFrames

  • Mapping Replace

  • Rename Index

  • Binning,Outliers,Permutation

  • GroupBy on DataFrames, GroupBy on Dict and Series

  • Splitting Applying and Combining

  • Cross Tabulation

Data Visualization

  • Installing Seaborn

  • Histograms

  • Kernel Density Estimate Plots

  • Combining Plot Styles

  • Box and Violin Plots ,Regression Plots

  • Heatmaps and Clustered Matrices

Introduction to Machine Learning

  • Applications of Machine Learning

  • Supervised vs Unsupervised Learning

  • Python libraries suitable for Machine Learning

Unsupervised Learning

  • K-Means Clustering

  • Hierarchical Clustering

  • Density-Based Clustering

Why Python is the Best Language for Your Career

Python has become one of the most in-demand programming languages due to its versatility, ease of use, and vast ecosystem of libraries. Here's why Python could be your best career choice:

  • Easy to Learn, Write, and Use

  • High Demand in the Job Market

  • Versatile Across Multiple Domains

  • Extensive Libraries and Frameworks

  • Ideal for AI and Machine Learning

  • Excellent for Rapid Prototyping

  • Massive Community Support

  • Future-Proof Language

  • Open-Source and Cost-Effective

  • Cross-Platform and Extensible

Project