Data Science and Machine Learning: A Practical Guide

Data Science and Machine Learning: A Practical Guide udemy course free download

Dive Deep into Data Analysis, Visualization, and Predictive Modeling – Excel in the World of Data Science

Unlock the Power of Python for Data Science and Visualization

Welcome to a comprehensive Python programming course tailored by Selfcode Academy for data science and visualization enthusiasts. Whether you're a beginner or looking to expand your skill set, this course will equip you with the knowledge you need.

Master the Python Basics:

• Start from scratch with Python fundamentals.

• Learn about variables, data types, and the logic behind programming.

• Explore conditional statements and loops.

• Dive into essential data structures like lists, tuples, dictionaries, and sets.

• Discover the world of functions, including powerful lambda functions.

• Get familiar with Object-Oriented Programming (OOP) concepts.

Python's Role in Data Science:

• Transition to data science seamlessly.

• Manipulate dates and times using Python's datetime module.

• Tackle complex text patterns with regular expressions (regex).

• Harness the power of built-in Python functions.

• Embrace NumPy for efficient numerical computing.

• Master Pandas and its data structures, including Series and DataFrames.

• Acquire data cleaning skills to handle missing values and outliers.

• Excel at data manipulation with Pandas, including indexing, grouping, sorting, and merging.

• Dive into data visualization with Matplotlib to create compelling graphs.

Advanced Data Science and Visualization:

• Uncover insights through Exploratory Data Analysis (EDA) techniques.

• Automate data analysis with Pandas Profiling, DABL, and Sweetviz.

• Perfect your data cleaning and preprocessing techniques.

• Craft captivating visualizations using Seaborn.

• Create various plots, from lines and areas to scatter and violin plots with Plotly.

• Take your data to the map with geographical visualizations.

Statistics and Hypothesis Testing:

• Dive into descriptive statistics, including central tendency and dispersion.

• Master inferential statistics, covering sampling, confidence intervals, and hypothesis testing.

• Learn to conduct hypothesis tests using Python libraries.

Capstone Project:

• Apply your skills to a real-world data science project.

• Define a business problem and structure your analysis.

• Summarize your findings in a comprehensive report.

Upon completing this course, you'll have a strong foundation in Python programming for data science and visualization. You'll possess the expertise to clean, analyze, and visualize data, empowering you to make data-driven decisions confidently.

Don't miss this opportunity to embark on your data science journey.

Enroll now and unleash the potential of Python for data exploration and visualization!