Centre For Applied Machine
Learning & Data Science

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Analysis

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Algorithm

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Process

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Programming

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Solution

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Knowledge

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Mentorship  - Flexible Training -  100% Internship  -  Placement Opportunity  

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Hi, we’re CAMLDS

Our Vision is to create platform for continuous learning and mentorship in Applied Machine Learning (AML) and Data Science (DS) for All.

CAMLDS provide clean and consistent training and mentorship to positively impact lives through applied knowledge, research and project in a digitally transformed ecosystems

We are committed to;

Our corporate strategy

CAMLDS in conjunction with industry partnership network (IPN), students have access to and possess a sense of belonging in AML-DS and lifelong learning pathways that extend every industry and across the IT landscape through our well designed fast paced Accelerated Training, Incubation, Internship and Followership program.

  • Raising hundred thousands of AML-DS talents/practitioners in 5 years
  • Position West African as one of the top AML-DS talent destinations
  • Promote critical innovation to help advance future state-of-the-art socio-economic problems in Africa.

Training and Learning Track

The AML-DS full-time program begins with two weeks of hands-on online learning, which provides students with the foundational data skills they'll need to excel in the program. Students then participate in 10 weeks of on-campus, project-based learning, which emphasizes collaboration and outcome-based skills development.
Students have access to support from the educator team throughout the day and during dedicated work periods. They also have access to a wide variety of additional training resources and materials available at all hours of the day and at intervals through dedicated mentors(Technical/Business). For the AML-DS professional development courses, typically about one-third to one-half of the class is dedicated to challenge work and project time in which students can work directly and individually with the senior AML-DS scientist instructors and/or the AML-DS scientist technical assistance. The mentor also holds weekly online office hours for students who have questions. Also offers a range of career services, including portfolio development, mock interviews with current industry professionals, résumé and job search workshops, and office tours of leading tech companies. The six-step iterative model of education prioritizes hands-on, project-based learning.
None, but individual pre-work programs are designed to bring student skills up to speed in advance of the program. No background knowledge is required but students are required to do about 20 hours of "pre-work" by the week day of class. Also offers a beginner Foundation Program option that students may take to skip the pre-work. Also to mention that no background knowledge is required for introductory-level courses.
Once you have gained mastery over the concepts and applications we will prepare you for interviews for the core AML-DS Role through our specially created models of interview preparations questions, we will teach students how to crack different types of questions. Subsequently, Students will have the opportunity to be placed on internship and have access to basic stipend from the 4th month.

Individual

Data Science Foundation: The Python Techniques

  • 8 weeks
  • Beginner
4 Projects
4.6

Python: Introduction to Python for beginners

  • 4 weeks
  • Beginner
2 Projects
4.9

Django: Build anything Web application with Python

  • 4 weeks
  • Intermediate
2 Projects
4.6

Figma/Adobe XD: Jump start application designs

  • 4 weeks
  • Beginner
2 Projects
4.8

Build Modern Static and Dynamic Web Sites

  • 4 weeks
  • Beginner
2 Projects
4.9

Vue.JS: How to easily create website with Vue

  • 4 weeks
  • Intermediate
2 Projects
4.5

Python Automation: Routine Task with Python

  • 4 weeks
  • Intermediate
6 Projects
4.8

@CAMLDS,

During the program, students work on commercial data science problems with companies, which include startups, SMEs, charities, Non-Governmental Organizations (NGO), Governments, and large multinational companies. There will be a huge range of different projects, and students' preferences will be taken into consideration.

Machine Learning

Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead

Data Science

Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data

Generative AI

Generative Artificial Intelligence fuels creativity, enabling personalized content and experiences, unlocking new avenues for entertainment, art, and self-expression appealing to Gen Z's digital-native sensibilities.

NLP / NLU

Natural language processing (NLP) and Natural Language Understanding (NLU) are subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages

Projects

First and foremost, we Identify problems that affect our society and can be solved using machine learning or data science modeling and techniques. From amongst the problems identified we evaluate, prioritize and work on projects to solve them. Every learner is expected to demo a capstone project at the end of the Cohort depending on the learning track.

AML, DS & AI based Projects

Case Studies

All core features, including:

  • Personalized ML Voice Assistant
  • Movie Recommendation Engine
  • Sentimental Analysis
  • Stock's Prediction
  • Object Recognition
  • Plant Disease Detection
  • Signature Prediction System
  • Business Automation with NLU
  • Skin Cancer Detection
  • Social Impact COVID-19 Intervention

IoT based Projects

Case Studies

Hardware Based Inetgration

  • Home Automation
  • Face Recognition Door Lock
  • Face Recognition Attendance System
  • Smart Mirror with Home Automation
  • Smart Security System

Languages, systems, and tools learned

Tech Stack

We organize structured study groups around core ML and DS fields like Machine Learning, Computer Vision (CV) and Natural Language Processing (NLP).

  • HTML / CSS / JavaScript100%
    Canva 55%
    Python 100%
    Git protocol, Bash, Linux 100%
    Flask / Django / PyQT 90%
    Arduino 55%
    Raspberry Pi 90%
    IoT 75%
    Automation 55%
    Tensorflow / Keras / PyTorch 90%

Team

Collins Onyemaobi

Co-Organizer

Terngu Orafa

Business Developer

Ryan Tao

Engineering Partner

Chidiamara Fiola

Business Strategist

Call For Volunteer Instructors

Help us build the Machine Learning and Data Science Community in Nigeria

Sign up as a Volunteer