Python for Data Science

Apply Python to real-world data problems. You will master NumPy, Pandas, Matplotlib, Seaborn, and Scikit-learn to perform data wrangling, exploratory data analysis and build machine learning models from scratch.

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trending_up intermediate Level

layers 5 Modules

Created by Test Instructor

Course Content

5 Modules • 25 Lessons

play_circle ML Workflow Overview

play_circle Linear and Logistic Regression

play_circle Decision Trees and Random Forest

play_circle Model Evaluation Metrics

play_circle Feature Engineering

description Capstone: Titanic Prediction

play_circle ndarray and dtypes

play_circle Array Indexing and Slicing

play_circle Broadcasting and Vectorization

play_circle Linear Algebra with NumPy

description NumPy Practice

play_circle Series and DataFrames

play_circle Reading CSV, Excel and JSON

play_circle Data Cleaning and Missing Values

play_circle Filtering, Grouping, Aggregation

play_circle Merging and Joining DataFrames

description Pandas EDA Project

play_circle Course Overview Preview

play_circle List Comprehensions and Generators Preview

play_circle Lambda, map, filter, reduce

play_circle Working with Files and CSV

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Test Instructor

Instructor

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NRS 90

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layers 5 modules • 25 lessons
ondemand_video On-demand video lessons
all_inclusive Full lifetime access
emoji_events Certificate of completion

NRS 90

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