Masterclass in Applied Python for Machine Learning & Strategic Data Analytics

Module 1: Foundation of Python for Data Analytics

ü  Introduction to Jupyter Notebooks and VS Code environment

ü  Python data structures: Lists, Dictionaries, and Tuples

ü  Control flow, loops, and functional programming

ü  NumPy fundamentals: N-dimensional arrays and vectorization

ü  Practical Session: Setting up the environment and performing basic mathematical operations on large datasets.

Module 2: Advanced Data Manipulation with Pandas

ü  Loading data from CSV, Excel, and SQL databases

ü  Data cleaning: Handling missing values and duplicates

ü  Multi-indexing and pivoting for complex reporting

ü  Merging, joining, and concatenating dataframes

ü  Practical Session: Cleaning and merging a fragmented retail dataset for analysis.

Module 3: Exploratory Data Analysis and Visualization

ü  Statistical summarization of numerical and categorical data

ü  Customizing plots with Matplotlib

ü  Statistical data visualization with Seaborn

ü  Identifying outliers and correlation patterns

ü  Practical Session: Creating a comprehensive visual dashboard to identify trends in consumer behavior.

Module 4: Principles of Machine Learning and Pre-processing

ü  The Machine Learning workflow: Train/Test split and Cross-validation

ü  Feature scaling: Normalization vs. Standardization

ü  Encoding categorical variables: Label Encoding and One-Hot Encoding

ü  Feature engineering: Creating new variables from existing data

ü  Practical Session: Preparing a raw dataset for model readiness using Scikit-Learn pipelines.

Module 5: Supervised Learning: Regression Analysis

ü  Simple and Multiple Linear Regression

ü  Evaluating regression models: R-squared, MSE, and MAE

ü  Polynomial regression for non-linear relationships

ü  Regularization techniques: Ridge and Lasso

ü  Practical Session: Building a predictive model to forecast real estate prices.

Module 6: Supervised Learning: Classification Techniques

ü  Logistic Regression for binary outcomes

ü  Decision Trees and Random Forests

ü  K-Nearest Neighbors (KNN) algorithm

ü  Support Vector Machines (SVM)

ü  Practical Session: Developing a classification model to predict customer churn.

Module 7: Unsupervised Learning: Clustering and Association

ü  K-Means clustering and the Elbow method

ü  Hierarchical clustering and Dendrograms

ü  Market Basket Analysis and Association Rules

ü  Identifying patterns in unlabeled data

ü  Practical Session: Segmenting a customer base into distinct groups for targeted marketing.

Module 8: Model Evaluation and Hyperparameter Tuning

ü  Confusion Matrix, Precision, Recall, and F1-Score

ü  ROC Curves and AUC (Area Under the Curve)

ü  Grid Search and Random Search for parameter optimization

ü  Dealing with imbalanced datasets (SMOTE technique)

ü  Practical Session: Optimizing a Random Forest model to achieve maximum accuracy and recall.

Module 9: Dimensionality Reduction and Feature Selection

ü  The Curse of Dimensionality

ü  Principal Component Analysis (PCA)

ü  Recursive Feature Elimination (RFE)

ü  Feature importance visualization

ü  Practical Session: Reducing a high-dimensional dataset to its most significant components without losing information.

Module 10: Machine Learning Project Lifecycle and Deployment

ü  Model persistence: Saving and loading models using Joblib/Pickle

ü  Introduction to Model APIs and Flask/Streamlit for deployment

ü  Ethics in AI: Bias detection and fairness

ü  Course review and best practices for the industry

ü  Practical Session: Deploying a final predictive model as a functional web application.

About Our Trainers

Our trainers are seasoned Data Scientists and Industry Consultants with over 10 years of experience in deploying Machine Learning solutions across Finance, Healthcare, and Telecommunications sectors. They hold advanced degrees in Computer Science and Statistics and are certified Python developers who bring practical, "in-the-trenches" knowledge to the classroom.

Quality Statement

Phoenix Center for Policy, Research and Training is committed to excellence. We ensure that our curriculum is updated quarterly to reflect the latest advancements in the Python ecosystem and Machine Learning libraries. We guarantee a high-impact learning experience through small class sizes and personalized mentorship.

Tailor-Made Courses

We understand that every organization has unique c⁸hall⁹enges and opportunities as well as unique training needs. Phoenix Training Center offers tailor-made courses designed to address specific requirements and challenges faced by your team or organization. Whether you need a customized curri¹⁰culum, a specific duration, or on-site delivery, we can adapt our expertise to provide a training solution that perfectly aligns with your objectives. For further inquiries, please contact us on Tel: +254720272325 / +254737296202 or Email training@phoenixtrainingcenter.com

Admission Criteria

ü  Participants should be reasonably proficient in English. 

ü  Applicants must live up to Phoenix Center for Policy, Research and Training admission criteria.

Terms and Conditions

ü  Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

ü  What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

ü  Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

ü  The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

ü  Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@phoenixtrainingcenter.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training. Or call us on +254720272325 / +254737296202

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

ü  Groups of 5 People and Above – Cheque Payments to: Phoenix Center for Policy, Research and Training Limited should be paid in advance, 5 days to the training.

ü  Invoice: We can send a bill directly to you or your company.

ü  Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

ü  Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

ü  Participants may cancel attendance 14 days or more prior to the training commencement date.

ü  No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Accommodation and Airport Transfer

For physical training attendees, we can assist with recommendations for accommodation near the training venue. Airport pick-up services can also be arranged upon request to ensure a smooth arrival. Please inform us of your travel details in advance if you require these services. For reservations contact the Training Officer on Email: training@phoenixtrainingcenter.com or on Tel: +254720272325 / +254737296202