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What You'll Learn

Master Python for advanced data analysis and machine learning. Learn to build complex models, implement advanced algorithms, and extract valuable insights from large datasets.

Course Benefits
Industry Certification

Internationally recognized qualification

Expert Instructors

Learn from industry professionals

Dedicated Support

Assistance during and after training

Practical Skills

Apply knowledge immediately

Comprehensive 10-day curriculum with all materials included
Hands-on exercises and real-world case studies
Valuable networking opportunities with peers and experts
Post-course resources and refresher materials
Training on Python for Advanced Data Analysis and Machine Learning - Course Cover Image
Duration 10 Days
Level Advanced
Format In-Person

Course Overview

Featured

This course delves into the advanced techniques of data analysis using Python, tailored for professionals seeking to enhance their analytical skills. It covers various aspects of data manipulation, visualization, statistical analysis, and machine learning using Python's powerful libraries. By the end of the course, participants will be able to handle complex datasets, perform sophisticated analyses, and derive actionable insights to inform decision-making processes.

Course Duration

10 Days

Who Should Attend

  • Data analysts and scientists looking to deepen their Python skills.
  • Professionals in finance, healthcare, marketing, and other data-intensive fields.
  • Academics and researchers requiring advanced data analysis capabilities.
  • IT professionals and developers interested in data science.
  • Individuals with a basic understanding of Python and data analysis concepts.

Course Impact

Organizational Impact

  • Enhance predictive capabilities and strategic decision-making through machine learning.

  • Improve operational efficiency by automating complex data analysis tasks.

  • Foster a data-driven culture to uncover trends, boost profitability, and strengthen competitive position.

Personal Impact

  • Gain cutting-edge skills in data science and machine learning.

  • Advance toward senior roles in data science, ML engineering, or technical leadership.

  • Contribute to organizational success with predictive solutions and data-driven recommendations.

  • Build confidence to lead and champion advanced analytics initiatives.

Course Objectives

By the end of this course, participants will be able to:

  • Enhance Python programming skills for advanced data analysis.
  • Master the use of key Python libraries such as NumPy, Pandas, Matplotlib, Seaborn, and Scikit-learn.
  • Develop proficiency in data cleaning, transformation, and preprocessing techniques.
  • Perform advanced statistical analyses and hypothesis testing.
  • Implement machine learning models for predictive analysis.
  • Visualize complex datasets using advanced plotting techniques.
  • Understand and apply time series analysis and forecasting methods.
  • Optimize data analysis workflows for efficiency and scalability.
  • Integrate Python with other data tools and environments.
  • Prepare participants to handle real-world data analysis challenges with confidence.

Course Outline

Module 1: Python Fundamentals for Data Analysis

  • Deep dive into NumPy: array operations, linear algebra, random number generation
  • Pandas: advanced data manipulation, time series analysis, performance optimization

Module 2: Exploratory Data Analysis (EDA) and Feature Engineering

  • In-depth EDA techniques: correlation analysis, hypothesis testing, outlier detection
  • Feature selection, creation, and transformation for model building

Module 3: Statistical Modeling with Python

  • Linear regression, logistic regression, and model evaluation
  • Time series analysis: ARIMA, forecasting
  • Hypothesis testing and statistical inference

Module 4: Machine Learning Foundations

  • Supervised and unsupervised learning overview
  • Model evaluation metrics and cross-validation
  • Hyperparameter tuning and model selection

Module 5: Classification Algorithms

  • Decision trees, random forests, support vector machines
  • Model interpretation and explainability

Module 6: Clustering Algorithms

  • K-means, hierarchical clustering, DBSCAN
  • Cluster evaluation and visualization

Module 7: Natural Language Processing (NLP)

  • Text preprocessing, tokenization, stemming, and lemmatization
  • Sentiment analysis, text classification, and topic modeling

Module 8: Deep Learning with Python

  • Introduction to neural networks and deep learning
  • Building and training neural networks using TensorFlow/Keras
  • Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN)

Module 9: Big Data Processing with Python

  • Introduction to Apache Spark and PySpark
  • Distributed data processing and analysis
  • Handling large datasets efficiently

Module 10: Data Visualization and Communication

  • Advanced data visualization techniques with Plotly and Seaborn
  • Interactive dashboards and storytelling
  • Effective communication of data insights to stakeholders

Prerequisites

No specific prerequisites required. This course is suitable for beginners and professionals alike.

Course Administration Details

Customized Training

This training can be tailored to your institution needs and delivered at a location of your choice upon request.

Requirements

Participants need to be proficient in English.

Training Fee

The fee covers tuition, training materials, refreshments, lunch, and study visits. Participants are responsible for their own travel, visa, insurance, and personal expenses.

Certification

Upon successful completion of this course, participants will be issued with a certificate from Ideal Workplace Solutions certified by the National Industrial Training Authority (NITA) under License NO: NITA/TRN/2734.

Accommodation

Accommodation can be arranged upon request. Contact via email for reservations.

Payment

Payment should be made before the training starts, with proof of payment sent to outreach@idealworkplacesolutions.org.

For further inquiries, please contact us on details below:

Register for the Course

Select a date and location that works for you.

In-Person Training Schedules


January 2026
Date Days Venue Fee (VAT Incl.) Register
5 Jan - 16 Jan 2026 10 days Nairobi, Kenya KES 198,000 | USD 2,800 Enroll Now
5 Jan - 16 Jan 2026 10 days Cape Town, South Africa USD 7,500 Enroll Now
5 Jan - 16 Jan 2026 10 days Dubai, United Arabs Emirates USD 8,000 Enroll Now
5 Jan - 16 Jan 2026 10 days Zanzibar, Tanzania USD 4,400 Enroll Now
12 Jan - 23 Jan 2026 10 days Mombasa, Kenya KES 230,000 | USD 3,000 Enroll Now
12 Jan - 23 Jan 2026 10 days Kigali, Rwanda USD 3,800 Enroll Now
12 Jan - 23 Jan 2026 10 days Accra, Ghana USD 7,200 Enroll Now
12 Jan - 23 Jan 2026 10 days Kampala, Uganda USD 3,800 Enroll Now
19 Jan - 30 Jan 2026 10 days Dar es Salaam, Tanzania USD 4,300 Enroll Now
19 Jan - 30 Jan 2026 10 days Johannesburg, South Africa USD 6,500 Enroll Now
19 Jan - 30 Jan 2026 10 days Nakuru, Kenya KES 210,000 | USD 2,800 Enroll Now
19 Jan - 30 Jan 2026 10 days Dakar, Senegal USD 6,000 Enroll Now
26 Jan - 6 Feb 2026 10 days Pretoria, South Africa USD 6,300 Enroll Now
26 Jan - 6 Feb 2026 10 days Kisumu, Kenya KES 210,000 | USD 3,000 Enroll Now
26 Jan - 6 Feb 2026 10 days Naivasha, Kenya KES 210,000 | USD 2,800 Enroll Now
26 Jan - 6 Feb 2026 10 days Arusha, Tanzania USD 4,300 Enroll Now
5 Jan - 16 Jan 2026
10 days
Venue:
Nairobi, Kenya
Fee (VAT Incl.):
KES 198,000
USD 2,800
Enroll Now
5 Jan - 16 Jan 2026
10 days
Venue:
Cape Town, South Africa
Fee (VAT Incl.):
USD 7,500
Enroll Now
5 Jan - 16 Jan 2026
10 days
Venue:
Dubai, United Arabs Emirates
Fee (VAT Incl.):
USD 8,000
Enroll Now
5 Jan - 16 Jan 2026
10 days
Venue:
Zanzibar, Tanzania
Fee (VAT Incl.):
USD 4,400
Enroll Now
12 Jan - 23 Jan 2026
10 days
Venue:
Mombasa, Kenya
Fee (VAT Incl.):
KES 230,000
USD 3,000
Enroll Now
12 Jan - 23 Jan 2026
10 days
Venue:
Kigali, Rwanda
Fee (VAT Incl.):
USD 3,800
Enroll Now
12 Jan - 23 Jan 2026
10 days
Venue:
Accra, Ghana
Fee (VAT Incl.):
USD 7,200
Enroll Now
12 Jan - 23 Jan 2026
10 days
Venue:
Kampala, Uganda
Fee (VAT Incl.):
USD 3,800
Enroll Now
19 Jan - 30 Jan 2026
10 days
Venue:
Dar es Salaam, Tanzania
Fee (VAT Incl.):
USD 4,300
Enroll Now
19 Jan - 30 Jan 2026
10 days
Venue:
Johannesburg, South Africa
Fee (VAT Incl.):
USD 6,500
Enroll Now
19 Jan - 30 Jan 2026
10 days
Venue:
Nakuru, Kenya
Fee (VAT Incl.):
KES 210,000
USD 2,800
Enroll Now
19 Jan - 30 Jan 2026
10 days
Venue:
Dakar, Senegal
Fee (VAT Incl.):
USD 6,000
Enroll Now
26 Jan - 6 Feb 2026
10 days
Venue:
Pretoria, South Africa
Fee (VAT Incl.):
USD 6,300
Enroll Now
26 Jan - 6 Feb 2026
10 days
Venue:
Kisumu, Kenya
Fee (VAT Incl.):
KES 210,000
USD 3,000
Enroll Now
26 Jan - 6 Feb 2026
10 days
Venue:
Naivasha, Kenya
Fee (VAT Incl.):
KES 210,000
USD 2,800
Enroll Now
26 Jan - 6 Feb 2026
10 days
Venue:
Arusha, Tanzania
Fee (VAT Incl.):
USD 4,300
Enroll Now

Request Custom Training


We offer customized training solutions tailored to your organization's specific needs:

  • Training at your preferred location
  • Customized content to address your specific challenges
  • Flexible scheduling to accommodate your team
  • Cost-effective solution for training multiple employees
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Frequently Asked Questions

Find answers to common questions about this course

The goal is to elevate your Python skills, equipping you to perform complex data analysis, build advanced machine learning models, and extract sophisticated, data-driven insights from your datasets.
Python offers a rich ecosystem of specialized libraries like Pandas, NumPy, and Scikit-learn that provide powerful, high-performance tools for complex data manipulation and analysis.
You'll master libraries like TensorFlow and PyTorch for deep learning, Scikit-learn for advanced modeling, and the Matplotlib and Seaborn libraries for sophisticated data visualization.
You'll learn to build and apply advanced models such as support vector machines (SVMs), random forests, and neural networks for complex classification, regression, and forecasting tasks.
By applying advanced machine learning, you can uncover subtle patterns, make highly accurate predictions, and automate complex analytical tasks, enabling a new level of data-driven insight.
Training on Python for Advanced Data Analysis and Machine Learning

Next class starts 5 Jan 2026

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