Learn Data Science and Build Intelligent Data Models
Discover how data scientists transform raw data into predictive insights.
Course Overview
An advanced programme covering statistical modelling, machine learning algorithms, and real-world applications of data science across industries including finance, healthcare, and technology.
What You Will Learn
Build and deploy machine learning models
Apply statistical analysis to real problems
Work with large, complex datasets
Present findings to technical audiences
Learning Modules
Module 1: Statistics and Data Science
Core statistical foundations for data science.
- Descriptive statistics
- Population and sample
- Inferential statistics
- Hypothesis testing
- Statistical tests
- Regression and correlation concepts
- Central Limit Theorem
- Law of Large Numbers
- Outliers and influence
- Resampling methods
Module 2: Probability
Probability principles for modeling uncertainty.
- Basic probability concepts
- Basic probability rules
- Conditional probability
- Independent and dependent events
- Mutually exclusive events
- Bayes' Theorem
Module 3: Python Programming (Beginner Level)
Programming essentials for data science workflows.
- Syntax
- Variables and data types
- Data structures
- Conditional statements
- Loops
- Functions
- Python libraries
Module 4: Python Libraries for Data Science
Use common libraries for analysis and visualization.
- NumPy
- Pandas
- Matplotlib
- Seaborn
Module 5: EDA with NumPy and Pandas
Prepare and explore datasets for insights.
- Data cleaning
- Data manipulation
- Exploratory data analysis
- Outlier detection
Module 6: Machine Learning
Understand and build basic ML workflows.
- Introduction to machine learning
- Basic concepts of machine learning
- Machine learning pipeline
- Introduction to scikit-learn
- Machine learning algorithms
- Model optimization
Module 7: Deep Learning
Introduction to deep learning concepts and applications.
- Natural language processing
- Convolutional neural networks
Tools you will use
Skills You Will Gain
Statistical thinking- Model evaluation
- Python programming
- Research methods
Career Opportunities
Taking this course can lead to careers in various industries, including healthcare, business, and technology.
