Introduction To Machine Learning

Introduction To Machine Learning (IML001) is offered as a CERTIFICATE course examined by FINSTOCK EVARSITY COLLEGE. A certificate of completion is issues upon completion of this course. For more information about this course, use the tabs below to navigate.

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Entry Requirements

Duration: 1 Months

Delivery Method: Online

Fee Structure

Full Course Fees
Registration Fee KES 1,000.00 ($ 10.00)
Certification Fee KES 0.00 ($ 0.00)
Administration Fee KES 0.00 ($ 0.00)
Internal Exam Fee KES 0.00 ($ 0.00)
External Exam Fee KES 0.00 ($ 0.00)
Examining Body Membership Fee * KES 0.00 ($ 0.00)
Tuition Fee KES 5,000.00 ($ 50.00)
Fees Totals KES 6,000.00 ($ 60.00)
* Examining Body Membership Fee may be payable through us or directly to the Examining Body

All Fees are payable in lumpusm or in installments, for details see below.
Breakdown per semester,

Trimester Total Per Trimester
Trimester 1KES 6,000.00 ($ 60.00)
TotalKES 6,000.00 ($ 60.00)

NB: Fees are payable in 3 installments as detailed below:

The trimester fees of KES 6,000.00 ($ 60.00) is payable in 3 installments of KES 2,000.00 ($ 20.00)

Course Requirements

You can also benefit from the resource below

Introduction to Machine Learning

Introduction to Machine Learning Professional Level

Practical Requirements (where applicable)

For courses that require practicals, a separate fee is chargable (not included in fee structure above) as follows:

  • Short courses - KES 5,000
  • Certificate courses - KES 7,500
  • Diploma courses - KES 10,000

Course Units/Overview


Unit IDUnit Name
IML001Introduction To Machine Learning

Course Description

Introduction to Machine Learning (CIAL001) is a comprehensive online short-term course offered by Finstock Evarsity College.  Introduction to Machine Learning course duration is one month. The examining body is Finstock Evarsity College. A certificate of completion is issued upon completion of the course.

Course Overview

  •  Introduction to Machine Learning course offers an in-depth introduction to concepts and methods for machine learning. The Emphasis will be on machine learning algorithms and applications and broad overview of underlying principles.
  • The training is designed for people who are new to Machine Learning. You will learn the basics of Machine Learning algorithms and techniques and their applications, and the relationship between Machine Learning, algorithms and programming as well as general questions related to analysing and handling large data sets.
  • Through hand-on practice and exercises, this courseware will cover what Learning Algorithms are, basic machine learning concepts and examples, basic probability notions, decision trees, element of learning theory, support vector machines, on-line learning, Bayesian inference, Kernel methods, logistic regression, introduction to reinforcement learning, regression, ensemble methods, density estimation, clustering, dimensionality reduction, nearest neighbour algorithm, ranking and career advice from experts about learning and starting career in Programming and machine learning.
  • This training will also use several public software libraries and data sets to illustrate the application of learning algorithms and demonstrate Algorithms in action with a mini project.
  • After taking this course, you are will be confident and empowered with knowledge, skills and abilities to advance to more challenging Learning Algorithms specializations  .

What are the Entry Requirement to Study for Introduction to Machine Learning ?

To enroll and study the Introduction to Machine Learning Course, a student should have a minimum of D Minus (D-) in their KCSE exams.

Mode of Delivery

The mode of delivery is Online Learning which means that one can study from home and/or the office. Our Program employs a variety of self-instructional electronic and online self-study materials, such as; written self-instructional study modules, online interactive devices, and self-tests, cloud-based content, videos of lectures mediated technical learning materials e.g., audio-visual and e-learning materials

Who Can Study Introduction to Machine Learning Course?

  • Students and Educators
  • Computer support specialist
  • IT analysts and IT security specialist
  • Programmers, Software and Web developers
  • Introduction to Machine Learning and computer network experts
  • Network and database Administrators and consultants in computing
  • Skilled traders

Why Study Introduction to Machine Learning at Finstock Evarsity College

  • To maximize take-home value from your investment, the course will draw on the skills and experience of seasoned professionals who have vast real-world experience and are experts in delivering online and instructor-led training programs.
  • The course teaching mode is done in a more simplified, engaging, personalized and professional ways using simple English to ensure maximum understanding, comprehension and retention of information presented. Moreover, the course is developed after extensive research and is aligned to global best practices in computer and IT globally and benchmarks.
  • The course will have many practical sessions that will give you an opportunity to practice and experience course-related practical and fun activities. These practical sessions will be supplemented by short lectures and a very comprehensive set of notes in order to understand every concept and part of this course.
  • The course is filled with examples, projects, case studies, real-life problems, step-by-step instructions and online discussions in this area, course projects and images files as well as feedback to facilitate learning. Because of this, this training will prove invaluable for experienced learners or beginners who have had no prior formal training in IT.
  • By the end of the course, you will be able to: define what Introduction to Machine Learning is, how to approach a problem, gain proficiency in programming, learn core principle of backend and software development, understand database, data querying and processing, master the principles of data scraping, cleaning, manipulation and exploration, do research and discover appropriate learning algorithms to solve a problem, apply these algorithm on a high level to a problem that you have, understand and tackle computer vision problems after researching the problems, understand classification problem, understand machine learning algorithms used by leading tech companies, and understand machine learning models and  demonstrate how they are used to solve complex problems in real-life tasks and situations.
  • Upon completion, Introduction to Machine Learning certification will prove that you have a valuable, career advancement skill in IT field for both entry-level and established professional level in the public sector, voluntary sector, corporate sector or private sector.

 

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Course Instructor(s)

JANE MUTURI JANE MUTURI

Examining Body

FINSTOCK EVARSITY COLLEGE

FAQs

Q1. How many intakes are there?

There are three intakes in a year as follows:

Cohort

Name

Term Period

Months

Registration Window

January Intake

Trimester 1

Jan 1 — Apr 30

4

Anytime

May Intake

Trimester 2

May 1 — Aug 31

4

Anytime

September Intake

Trimester 3

Sep 1 — Dec 31

4

Anytime

Q2. In how many installments can I pay the fees?

Payments can be done in 3 installments as specified in the fee structure.

Q3. When can I sit for the exams?

  1. Internal exams are activated for students individually.
  2. External exams (where applicable) are booked one month after you complete the course.

Refer to the external examining body for more details and requirements before seating for their exams.

Q4: Is this college accredited/approved?

Yes. The college is approved under the ministry of education, through TVETA, and also through National Industrial Training Authority (NITA).


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