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What You'll Learn

Master AI, data science, and machine learning with Python. Build intelligent systems, analyze data, and make informed decisions.

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 5-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 Introduction to AI, Data Science & Machine Learning with Python - Course Cover Image
Duration 5 Days
Level Intermediate
Format In-Person

Course Overview

Featured

This comprehensive course is designed to equip professionals with the foundational skills and techniques needed to succeed in the rapidly growing field of data science. Participants will learn the data science lifecycle, from data analysis and visualization using Python and its libraries to preprocessing unstructured data and building AI/ML models. The training provides a strategic framework for applying these techniques to solve real-world problems.

Duration

5 Days

Who Should Attend:

  • Aspiring data scientists and machine learning engineers

  • Data analysts and business intelligence professionals

  • Managers and team leaders seeking to understand data-driven strategies

  • Professionals in marketing, finance, and operations

  • Anyone interested in a career in AI, data science, and analytics

Course Impact

Organisational Impact

  • Strengthens organisational capacity to leverage data-driven insights for strategic decision-making.

  • Enhances competitiveness by equipping teams with skills in AI, data science, and machine learning applications.

  • Reduces dependency on external consultants by building in-house expertise for data analysis and predictive modeling.

  • Improves operational efficiency through automation and intelligent systems powered by machine learning.

  • Supports innovation in products, services, and customer engagement through data-driven strategies.

Personal Impact

  • Equips participants with foundational skills in Python for data science, AI, and machine learning.

  • Builds confidence in applying key algorithms such as regression, classification, and clustering to solve problems.

  • Provides hands-on experience in real-world applications like customer churn prediction and recommendation systems.

  • Expands career opportunities in the rapidly growing fields of AI, data science, and analytics.

  • Empowers learners to build a strong portfolio of projects showcasing applied skills in AI and ML.

Course Objectives

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

  • Differentiate between Predictive AI and Generative AI.
  • Translate everyday business questions and problems into Machine Learning tasks to make data-driven decisions.
  • Use Python Pandas, Matplotlib & Seaborn libraries to explore, analyze, and visualize data from various sources, including the web, word documents, email, NoSQL stores, databases, and data warehouses.
  • Train a Machine Learning Classifier using different algorithmic techniques from the Scikit-Learn library, such as Decision Trees, Logistic Regression, and Neural Networks.
  • Re-segment your customer market using K-Means and Hierarchical algorithms to better align products and services to customer needs.
  • Discover hidden customer behaviors from Association Rules and build a Recommendation Engine based on behavioral patterns.
  • Investigate relationships & flows between people and business-relevant entities using Social Network Analysis.
  • Build predictive models of revenue and other numeric variables using Linear Regression.
  • Leverage continued support with after-course one-on-one instructor coaching and computing sandbox.

Course Outline

Module 1: The Strategic Role of a Data Scientist

  • Required technical and non-technical skillsets
  • Distinction between Data Scientist and Data Engineer
  • Full lifecycle of data science initiatives in an organization
  • Translating business questions into AI and ML models
  • Understanding data sources for analytical insights
  • Difference between Generative AI and Discriminative AI

Module 2: Data Manipulation and Visualization with Python

  • Introduction to Python for data science and engineering
  • Data import, export, and handling from diverse sources
  • Using Pandas for selecting, filtering, grouping, and applying functions
  • Managing duplicates, missing values, normalization, and scaling
  • Visual analytics using Pandas, Matplotlib, and Seaborn

Module 3: Natural Language Processing and Unstructured Data Analysis

  • Preprocessing web content, emails, and free-text data
  • Techniques such as stemming and removal of stop words
  • Building a term-document matrix (TDM)
  • Integrating Large Language Models (LLMs) in data analysis

Module 4: AI Ethics, Big Data Analytics and Professional Communication

  • Cloud-based analytics (Microsoft Azure, AWS, Google Cloud)
  • Ethical implications of AI developments
  • Communication responsibilities of a data scientist
  • Career development and continuous learning in the field

Module 5: Machine Learning Evaluation, Classification & Clustering Techniques

  • Overview of classification methods (e.g., logistic regression, neural networks)
  • Activation functions and their role in model development
  • Probability foundations of Naive Bayes classifiers
  • Model performance measures (ROC, AUC, precision, recall, confusion matrix)
  • Customer and product segmentation using clustering algorithms
  • K-Means and hierarchical clustering with Scikit-Learn
  • Clustering applications on unstructured data (tweets, emails, documents)

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 - 9 Jan 2026 5 days Nairobi, Kenya KES 99,000 | USD 1,400 Enroll Now
5 Jan - 9 Jan 2026 5 days Cape Town, South Africa USD 3,500 Enroll Now
5 Jan - 9 Jan 2026 5 days Dubai, United Arabs Emirates USD 4,000 Enroll Now
5 Jan - 9 Jan 2026 5 days Zanzibar, Tanzania USD 2,200 Enroll Now
12 Jan - 16 Jan 2026 5 days Mombasa, Kenya KES 115,000 | USD 1,500 Enroll Now
12 Jan - 16 Jan 2026 5 days Kigali, Rwanda USD 1,800 Enroll Now
12 Jan - 16 Jan 2026 5 days Accra, Ghana USD 5,950 Enroll Now
12 Jan - 16 Jan 2026 5 days Kampala, Uganda USD 2,200 Enroll Now
19 Jan - 23 Jan 2026 5 days Dar es Salaam, Tanzania USD 2,000 Enroll Now
19 Jan - 23 Jan 2026 5 days Johannesburg, South Africa USD 3,100 Enroll Now
19 Jan - 23 Jan 2026 5 days Nakuru, Kenya KES 105,000 | USD 1,400 Enroll Now
19 Jan - 23 Jan 2026 5 days Dakar, Senegal USD 3,500 Enroll Now
26 Jan - 30 Jan 2026 5 days Pretoria, South Africa USD 3,100 Enroll Now
26 Jan - 30 Jan 2026 5 days Kisumu, Kenya KES 105,000 | USD 1,500 Enroll Now
26 Jan - 30 Jan 2026 5 days Naivasha, Kenya KES 105,000 | USD 1,400 Enroll Now
26 Jan - 30 Jan 2026 5 days Arusha, Tanzania USD 2,000 Enroll Now
5 Jan - 9 Jan 2026
5 days
Venue:
Nairobi, Kenya
Fee (VAT Incl.):
KES 99,000
USD 1,400
Enroll Now
5 Jan - 9 Jan 2026
5 days
Venue:
Cape Town, South Africa
Fee (VAT Incl.):
USD 3,500
Enroll Now
5 Jan - 9 Jan 2026
5 days
Venue:
Dubai, United Arabs Emirates
Fee (VAT Incl.):
USD 4,000
Enroll Now
5 Jan - 9 Jan 2026
5 days
Venue:
Zanzibar, Tanzania
Fee (VAT Incl.):
USD 2,200
Enroll Now
12 Jan - 16 Jan 2026
5 days
Venue:
Mombasa, Kenya
Fee (VAT Incl.):
KES 115,000
USD 1,500
Enroll Now
12 Jan - 16 Jan 2026
5 days
Venue:
Kigali, Rwanda
Fee (VAT Incl.):
USD 1,800
Enroll Now
12 Jan - 16 Jan 2026
5 days
Venue:
Accra, Ghana
Fee (VAT Incl.):
USD 5,950
Enroll Now
12 Jan - 16 Jan 2026
5 days
Venue:
Kampala, Uganda
Fee (VAT Incl.):
USD 2,200
Enroll Now
19 Jan - 23 Jan 2026
5 days
Venue:
Dar es Salaam, Tanzania
Fee (VAT Incl.):
USD 2,000
Enroll Now
19 Jan - 23 Jan 2026
5 days
Venue:
Johannesburg, South Africa
Fee (VAT Incl.):
USD 3,100
Enroll Now
19 Jan - 23 Jan 2026
5 days
Venue:
Nakuru, Kenya
Fee (VAT Incl.):
KES 105,000
USD 1,400
Enroll Now
19 Jan - 23 Jan 2026
5 days
Venue:
Dakar, Senegal
Fee (VAT Incl.):
USD 3,500
Enroll Now
26 Jan - 30 Jan 2026
5 days
Venue:
Pretoria, South Africa
Fee (VAT Incl.):
USD 3,100
Enroll Now
26 Jan - 30 Jan 2026
5 days
Venue:
Kisumu, Kenya
Fee (VAT Incl.):
KES 105,000
USD 1,500
Enroll Now
26 Jan - 30 Jan 2026
5 days
Venue:
Naivasha, Kenya
Fee (VAT Incl.):
KES 105,000
USD 1,400
Enroll Now
26 Jan - 30 Jan 2026
5 days
Venue:
Arusha, Tanzania
Fee (VAT Incl.):
USD 2,000
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 provide a solid foundation in AI, Data Science, and Machine Learning using Python. You'll learn to analyze data, build predictive models, and understand how these technologies drive modern business decisions.
AI is the broad field of intelligent systems. Machine Learning is a subset of AI where computers learn from data. Data Science is a multi-disciplinary field that uses these tools to extract insights from data.
Python is the most popular language for these fields due to its simple syntax and powerful libraries. It allows you to focus on the concepts rather than complex code, making it a key for innovation.
No prior coding or data science experience is required. This course is designed for absolute beginners. It will provide you with the fundamental skills needed to start a career in these high-demand fields and build a foundation for more advanced training.
You'll learn core skills like data manipulation, exploratory data analysis, and building your first machine learning models. The training emphasizes a hands-on approach to using Python to solve real-world problems with professionalism.
Training on Introduction to AI, Data Science & Machine Learning with Python

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