### Course Overview
- **Course Title:** **Machine Learning & Python Data Science for Business and AI**
- **Instructor:** **Brighter Futures Hub**
- **Target Audience:**
- Business professionals seeking **data-driven decision-making** skills
- Students aiming to enter **AI, machine learning, or data science** fields
- Developers looking to expand skills in **Python for data analysis**
- Beginners with **no prior experience** in coding or statistics
- **Prerequisites:** **None**
### Curriculum Highlights
- **Key Topics Covered:**
- **Python fundamentals** for data science (lists, tuples, dictionaries, sets)
- **Key Python libraries**: **NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn**
- **Data manipulation** (merging, filtering, sorting, aggregating) with **Pandas**
- **Descriptive statistics** (mean, median, mode, variance, standard deviation)
- **Data visualization** using **Matplotlib and Seaborn**
- **Handling missing data** (imputation, deletion techniques)
- **Machine learning fundamentals**:
- **Supervised vs. unsupervised learning**
- **Linear regression & logistic regression** (theory, implementation, evaluation)
- **K-Nearest Neighbors (KNN)**
- **Clustering algorithms**: **K-Means, hierarchical clustering**
- **Feature selection methods** (filter, wrapper, embedded)
- **Ensemble techniques**:
- **Bagging (Random Forests, Bootstrap Aggregating)**
- **Boosting (AdaBoost, Gradient Boosting, XGBoost)**
- **Introduction to neural networks & deep learning** (structure, neurons, layers)
- **Key Skills Learned:**
- Writing **Python code** for **data analysis and AI tasks**
- Building and evaluating **machine learning models** (classification, regression, clustering)
- **Data cleaning, preprocessing, and visualization**
- Applying **AI and ML** to solve **real-world business problems**
- **Hyperparameter tuning** and **model performance assessment**
- Developing a **professional data science portfolio**
### Course Format
- **Duration:** **5.5 hours on-demand video**
- **Format:** **Self-paced online course** (lifetime access)
- **Resources:**
- **Mobile and TV access**
- **Certificate of completion**
- **Hands-on exercises** (no downloadable materials specified beyond video lectures)
### Additional Information
- **Instructor Rating:** **4.0** (340 reviews)
- **Students Enrolled:** **30,719+**
- **Focus:** **Practical, project-based learning** with **business and AI applications**
- **Outcome:** Ability to **implement machine learning models** and **translate data into actionable insights**
