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Machine Learning, Data Science and Generative AI with Python

An engaging and comprehensive course that provides a solid foundation in Data Science and Machine Learning with Python through practical projects and clear instruction.

access

Lifetime

level

Beginner

certificate

Certificate of completion

language

English

What will you in Machine Learning, Data Science and Generative AI with Python Course

  • Python Programming: Master Python essentials, including variables, data types, control flow, and functions.
  • Data Analysis & Manipulation: Utilize libraries like NumPy and Pandas for data cleaning, transformation, and analysis.
  • Data Visualization: Create compelling visualizations using Matplotlib, Seaborn, and Plotly.

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  • Machine Learning Algorithms: Implement algorithms such as Linear Regression, K-Nearest Neighbors, Decision Trees, Random Forests, and Support Vector Machines using Scikit-Learn.
  • Natural Language Processing (NLP): Develop spam filters and text classification models.
  • Deep Learning: Explore neural networks and Convolutional Neural Networks (CNNs) for image classification tasks.

Program Overview

Introduction to Python for Data Science

⏳ 1 hour

  • Setting up the Python environment.

  • Basic Python syntax and data structures.

Data Analysis with Pandas & NumPy

⏳ 2 hours

  • Data cleaning and preprocessing.

  • Exploratory Data Analysis (EDA).

  • Handling missing data and outliers.

Data Visualization Techniques

⏳ 1.5 hours

  • Creating static and interactive plots.

  • Visualizing distributions, correlations, and trends.

Supervised Learning Algorithms

⏳ 3 hours

  • Implementing and understanding Linear Regression, K-Nearest Neighbors, Decision Trees, and Random Forests.

  • Evaluating model performance using metrics like accuracy, precision, recall, and F1-score.

Unsupervised Learning Techniques

⏳ 2 hours

  • Applying K-Means Clustering and Hierarchical Clustering.

  • Dimensionality reduction using PCA.

Natural Language Processing (NLP)

⏳ 2 hours

  • Text preprocessing and tokenization.

  • Building spam filters and text classification models.

Deep Learning with Neural Networks

⏳ 3 hours

  • Understanding the basics of neural networks.

  • Implementing CNNs for image classification tasks.

Model Deployment & Best Practices

⏳ 1 hour

  • Saving and loading models.

  • Deploying models for real-world applications.

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Job Outlook

  • High Demand for Data Science Skills: Data Science and Machine Learning are among the most sought-after skills in the tech industry.

  • Career Opportunities: Proficiency in Python and machine learning opens doors to roles such as Data Scientist, Machine Learning Engineer, and AI Specialist.

  • Industry Adoption: Companies across various sectors, including finance, healthcare, and e-commerce, leverage data science for decision-making and automation.

9.7Expert Score
Highly Recommended
This course offers a comprehensive and hands-on approach to learning Data Science and Machine Learning with Python, making it ideal for both beginners and professionals looking to enhance their skills.
Value
9.6
Price
9.4
Skills
9.8
Information
9.9
PROS
  • Structured curriculum with practical projects.
  • Clear and engaging instruction by experienced instructors.
  • Real-world applications to reinforce learning.
  • Lifetime access to course materials.
CONS
  • Limited coverage of advanced deep learning topics.
  • No interactive speaking assessments or live feedback.

Specification: Machine Learning, Data Science and Generative AI with Python

access

Lifetime

level

Beginner

certificate

Certificate of completion

language

English

Machine Learning, Data Science and Generative AI with Python
Machine Learning, Data Science and Generative AI with Python
Course | Career Focused Learning Platform
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