ADVANCED DIPLOMA IN APPLIED DATA SCIENCE AND MACHINE LEARNING TECHNOLOGY
The Advanced Diploma in Applied Data Science and Machine Learning equips you with in-demand skills for data analysis, modeling, and problem-solving in various industries, involving hands-on learning and real-world case studies.
What you’ll learn
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Utilize essential data science libraries such as Pandas, NumPy, Matplotlib, and Seaborn.
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Differentiate between structured and unstructured data.
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Gain proficiency in Python programming language for data analysis.
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Understand the fundamental concepts of data science.
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Differentiate between data science, data engineering, and data analysis.
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Recognize the applications and industry impact of data science.
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Install Python and set up a development environment on Windows and macOS.
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Familiarize with Jupyter Notebook and use it for interactive data analysis.
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Explore and manipulate data using Pandas DataFrames.
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Create and manipulate Pandas Series for efficient data handling.
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Load datasets into Pandas and perform initial data inspection and cleaning.
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Transform and analyze data using Pandas methods.
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Visualize data using Matplotlib and Seaborn for insights and reporting.
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Utilize statistical techniques for data exploration and hypothesis testing.
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Define machine learning and its application in data science.
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Understand supervised, unsupervised, and reinforcement learning techniques.
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Preprocess data for machine learning models, including handling missing values and encoding categorical variables.
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Build, train, and evaluate machine learning models using scikit-learn.
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Measure model performance using metrics like accuracy, confusion matrix, and classification report.
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Deploy a machine learning model for real-time predictions and understand model interpretability techniques.
Who this course is for:
- Data Analysts and Engineers
- Aspiring Data Scientists
- Students and Graduates
- Professionals Transitioning Careers
- Entrepreneurs and Business Owners
- Anyone Curious About Data Science
Instructor
