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.
- 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
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Setting up the Python environment.
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Basic Python syntax and data structures.
Data Analysis with Pandas & NumPy
⏳ 2 hours
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Data cleaning and preprocessing.
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Exploratory Data Analysis (EDA).
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Handling missing data and outliers.
Data Visualization Techniques
⏳ 1.5 hours
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Creating static and interactive plots.
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Visualizing distributions, correlations, and trends.
Supervised Learning Algorithms
⏳ 3 hours
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Implementing and understanding Linear Regression, K-Nearest Neighbors, Decision Trees, and Random Forests.
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Evaluating model performance using metrics like accuracy, precision, recall, and F1-score.
Unsupervised Learning Techniques
⏳ 2 hours
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Applying K-Means Clustering and Hierarchical Clustering.
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Dimensionality reduction using PCA.
Natural Language Processing (NLP)
⏳ 2 hours
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Text preprocessing and tokenization.
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Building spam filters and text classification models.
Deep Learning with Neural Networks
⏳ 3 hours
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Understanding the basics of neural networks.
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Implementing CNNs for image classification tasks.
Model Deployment & Best Practices
⏳ 1 hour
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Saving and loading models.
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Deploying models for real-world applications.
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Job Outlook
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High Demand for Data Science Skills: Data Science and Machine Learning are among the most sought-after skills in the tech industry.
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Career Opportunities: Proficiency in Python and machine learning opens doors to roles such as Data Scientist, Machine Learning Engineer, and AI Specialist.
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Industry Adoption: Companies across various sectors, including finance, healthcare, and e-commerce, leverage data science for decision-making and automation.
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Applied Machine Learning in Python Course – Learn to implement machine learning models in Python with hands-on exercises, focusing on real-world data-driven problem solving.
Related Reading
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What Is Python Used For? – Explore the wide-ranging applications of Python in data science, AI, web development, and more.
