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 1 | KES 6,000.00 ($ 60.00) |
Total | KES 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
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 ID | Unit Name |
---|---|
IML001 | Introduction 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.
Tags
Introduction to Machine Learning Course, Introduction to Machine Learning proficiency certificate Course, Computer and Information Technology short-courses, best online courses in Kenya, Introduction to Machine Learning Finstock Evarsity college, Online courses, accredited online courses, online courses with downloadable certificates, freemium courses, short courses, professional development courses, Diploma and Certificate Courses, Marketable online courses, affordable online courses, short online courses with a certificate in Kenya, free short online courses with a certificate in Kenya, free online courses in Kenya 2022, online certificate courses in Kenya, Certificate Introduction to Machine Learning in Kenya, Concepts in IT colleges, Concepts in IT, Artificial Intelligence
Course Instructor(s)
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?
- Internal exams are activated for students individually.
- 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).
Course Reviews
Top Rated Reviews
No course reviews are available at the moment. Reviews are only submitted by students persuing the course. Reviews are subject to our terms and conditions.