Machine Learning & Data Intelligence Program (MLDIP)
2026 Pilot Cohort | 4-Month Structured Program
Train in data-driven problem solving, machine learning workflows, and intelligent system development.
Who is this Program For?
Aspiring Data Scientists
Starting their ML journey
ML Engineers
Entry–mid level professionals
Analysts
Transitioning into ML roles
Researchers
Technical researchers and innovators
Tools You Will Learn
Python
Programming for data and ML
NumPy
Numerical computing and arrays
Pandas
Data manipulation and analysis
Matplotlib
Data visualization and plotting
Scikit-learn
Machine learning algorithms
Streamlit
ML app deployment and UI
Git & GitHub
Version control and collaboration
Statistics
Statistical reasoning for ML
What You Will Learn
Python Programming
Write code for data analysis and ML
ML Models
Build, evaluate, and interpret models
EDA
Perform exploratory data analysis
Statistics
Apply statistics to ML problems
Deployment
Deploy basic ML applications
Communication
Communicate ML results clearly
Program Structure
Duration
4 Months (Teaching Phase)
Mode
Live Virtual Sessions
Projects
Mentored Capstone Project
Certification
iPace Data Academy Certificate
Course Descriptions
A. Python Fundamentals
Topics Covered:
- Python basics and syntax
- Data types and variables
- Control flow (if-else, loops)
- Functions and modules
B. Statistics for Machine Learning
Topics Covered:
- Probability theory and distributions
- Statistical estimation and inference
- Statistical thinking for ML
- Hypothesis testing basics
C. Introduction to Python Data Libraries
Topics Covered:
- NumPy for numerical operations
- Pandas for data handling
- Data structures and manipulation
- Basic data operations
D. Exploratory Data Analysis (EDA)
Topics Covered:
- Data cleaning and preprocessing
- Data visualization techniques
- Feature understanding and selection
- Insight generation from data
E. Git & GitHub for Data Projects
Topics Covered:
- Version control fundamentals
- Git commands and workflows
- GitHub repository management
- Collaboration and project management
F. Machine Learning Concepts & Workflow
Topics Covered:
- Supervised learning algorithms
- Unsupervised learning techniques
- Model evaluation and metrics
- ML pipelines and best practices
G. ML Model Deployment (Streamlit)
Topics Covered:
- Model packaging and serialization
- Deployment strategies
- Interactive ML apps with Streamlit
- Application testing and debugging
H. Cross-Program Seminars
Topics Covered:
- Responsible Use of AI (1 Day)
- Digital & Data Thinking (1 Day)
- Data Visualization & Interpretation (2 Days)
Certification
Official iPace Data Academy Certificate Template
Official Certificate
Recognized by iPace Data Academy and iPace Concepts
Verified Competence
Capstone project defense required for certification
Global Recognition
Comparable to top global certifications in data analytics
University Model
Rigorous academic standards with mentorship support
Tuition
Fee
₦150,000
Options
Installment plans available
Words from the Head of Program
"MLDIP transforms learners into elite data practitioners through rigorous academic workflows and applied research integration."
Instructors
Python & ML Instructors
Python Programming and ML Experts
Data Science Practitioners
Industry Data Science Experts
AI Ethics Experts
Research and AI Ethics Specialists
Industry Professionals
Invited Industry Experts
Ready to Start Your Journey?
Join the 2026 Pilot Cohort and transform your career with iPace Data Academy's structured, university-model education. Limited seats available for this exclusive program.
Program Starts
January 2026
Delivery Mode
100% Virtual (Live Sessions)
Certificate
Official iPace Data Academy Certificate
Support
24/7 Mentorship & Technical Support
Questions? Contact us at ipace2024@gmail.com or WhatsApp +2348111986185
