Complete Data science boot camp using Python

Data science & Machine learning – Pandas, Numpy, Matplotlib, Scikit learn, Supervised&Deep learning and Neural networks

What you’ll learn
Basics of Data science and Machine learning
Create their own Data model and prediction modelling
Data gathering and Data manipulation

Requirements
Basic Python knowledge
Willing to learn new tools

Description
End to end Implementation of Data science and Machine Learning model.From Data analysis and gathering to creating your own modelling will be covered as part of this course.Pandas:Creation of Data representationData filteringData frameworkSelection and viewingData ManipulationNumpy:Datatypes in NumpyCreating arrays and Matrix.Manipulation of data.Standard deviation and variance.Reshaping of Matrix.Dot functionMini-project using Numpy and Pandas packageMatplotlib:Creation Plots – Line, Scatter, bar and Histogram.Creating plots from Pandas and Numpy dataCreation of subplotsCustomization and saving plotsScikit Learn: Scikit-learn is a free, open-source Python library for machine learning. It offers simple, efficient tools for data analysis and modeling, including classification, regression, clustering, preprocessing, and model selection. Built on NumPy and SciPy, it features a consistent API and supports various popular algorithmsSupervised Learning: A machine learning method where models are trained using labeled data, meaning each input is paired with the correct output or label. The algorithm learns the relationship between inputs and outputs, enabling it to predict or classify new, unseen data accuratelySkills & ApplicationsImport, preprocess, and visualize real-world datasetsPerform statistical analyses efficientlyCreate reproducible analyses and effective visual storytellingThis course is ideal for beginners and intermediate learners aiming to build analytical and visualization skills necessary for data-driven decision making in science, business, and engineering.

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