Download the Machine Learning and Data Science syllabus PDF and Learn the latest concepts and techniques to become an expert in these high-demand fields. Download now and enhance your career prospects.
Data Science and Machine Learning (ML) applications have fueled the growth of world-renowned companies such as Netflix and Google, which rely on a data-driven approach to decision-making. Analytics Insight (2020) reports that approximately 77% of current devices are utilizing ML. To prepare for the digital era and remain competitive, organizations require skilled talent to leverage the exponential potential of data science and ML for automation, effective decision-making, and gaining an edge in the marketplace.
Data Science Syllabus PDF: Contents
This is just an overview. The PDF contains more detailed syllabus information on Data Science and Machine Learning.
Module 1: Introduction to Data Science
- Selecting rows/observations
- Rounding Number
- Selecting columns/fields
- Merging data
- Data aggregation
- Data munging techniques
Module 2: Introduction to Python
- What is Python?
- Why Python?
- Installing Python
- Python IDEs
- Jupyter Notebook Overview
Module 3: Python Basics
- Python Basic Data types
- Lists
- Slicing
- IF statements
- Loops
- Dictionaries
- Tuples
- Functions
- Array
- Selection by position & Labels
Module 4: Python Packages
- Pandas
- Numpy
- Sci-kit Learn
- Mat-plot library
Module 5: Importing Data
- Reading CSV files
- Saving Python data
- Loading Python data objects
- Writing data to CSV file
Module 6: Manipulating Data
- Selecting rows/observations
- Rounding Number
- Selecting columns/fields
- Merging data
- Data aggregation
- Data munging techniques
Module 7: Statistics Basics
- Central Tendency
- Probability Basics
- Standard Deviation
- Bias variance Tradeoff
- Distance metrics
- Outlier analysis
- Missing Value Treatment
- Correlation
Module 8: Error Metrics
- Classification
- Regression
Data Science Syllabus PDF: Download Here👇
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