Entry Requirements for Diploma In Data Science
C-
Duration: 12 Months
Delivery Method: Both Online & Physical
Fee Structure for Diploma In Data Science
| Full Course Fees | |
|---|---|
| Registration Fee | KES 1,000.00 ($ 10.00) |
| Certification Fee | KES 0.00 ($ 0.00) |
| Administration Fee | KES 5,000.04 ($ 50.00) |
| Internal Exam Fee | KES 14,999.94 ($ 150.00) |
| External Exam Fee | KES 0.00 ($ 0.00) |
| Examining Body Membership Fee * | KES 0.00 ($ 0.00) |
| Tuition Fee | KES 100,000.08 ($ 1,000.00) |
| Fees Totals | KES 121,000.00 ($ 1,210.00) |
| * 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 40,333.33 ($ 403.33) |
| Trimester 2 | KES 40,333.33 ($ 403.33) |
| Trimester 3 | KES 40,333.33 ($ 403.33) |
| Total | KES 121,000.00 ($ 1,210.00) |
NB: Fees are payable in 3 installments as detailed below:
The trimester fees of KES 40,333.33 ($ 403.33) is payable in 3 installments of KES 13,444.44 ($ 134.44)
Course Requirements for Diploma In Data Science
- All Fees are payable in installements, for details check FAQs.
- Digital (downloadable) certificates are available. Printing and shipping of hardcopy certificate can be done at a cost of KES 2,000 ($ 20).
Practical Requirements for Diploma In Data Science (where applicable)
The cost of practicals, internships or industrial requirements is KES 30,000 ($ 300) and only applies to courses that require practicals.
Course Units/Overview for Diploma In Data Science
SEMESTER 1
Module I
-
Introduction to Data Science
-
Mathematics for Data Science
-
Statistics for Data Science
-
Programming for Data Science (Python/R)
-
Data Collection and Management
-
Database Systems and SQL
-
Data Cleaning and Preprocessing
SEMESTER 2
Module II
-
Data Cleaning and Preprocessing
-
Exploratory Data Analysis (EDA)
-
Data Visualization and Communication
-
Machine Learning Fundamentals
-
Advanced Machine Learning Techniques
-
Big Data Technologies and Tools
SEMESTER 3
Module III
-
Cloud Computing for Data Science
-
Artificial Intelligence and Deep Learning
-
Data Ethics, Security, and Governance
-
Business Analytics and Decision Making
-
Capstone Project in Data Science
-
Emerging Trends in Data Science
| Unit ID | Unit Name |
|---|---|
| DIDS001 | Introduction To Data Science |
| DIDS002 | Mathematics For Data Science |
| DIDS003 | Statistics For Data Science |
| DIDS004 | Programming For Data Science |
| DIDS005 | Data Collection And Management |
| DIDS006 | Database Systems And SQL |
| DIDS007 | Data Cleaning And Preprocessing |
| DIDS008 | Exploratory Data Analysis |
| DIDS009 | Data Visualization And Communication |
| DIDS010 | Machine Learning Fundamentals |
| DIDS011 | Advanced Machine Learning Techniques |
| DIDS012 | Big Data Technologies And Tools |
| DIDS013 | Cloud Computing For Data Science |
| DIDS014 | Artificial Intelligence And Deep Learning |
| DIDS015 | Data Ethics, Security, And Governance |
| DIDS016 | Business Analytics And Decision Making |
| DIDS017 | Capstone Project In Data Science |
| DIDS018 | Emerging Trends In Data Science |
Course Description for Diploma In Data Science
Diploma in Data Science
COURSE OVERVIEW
The Diploma in Data Science at Finstock Evarsity College is a comprehensive, industry-oriented program designed to equip learners with the essential knowledge and practical skills needed to collect, process, analyze, and visualize data to inform decision-making. This course covers foundational and intermediate concepts in statistics, programming, machine learning, data mining, and data visualization, aligned with current industry standards.
Through a practical, hands-on approach, learners gain experience in using popular data science tools such as Python, R, SQL, and cloud-based platforms. The program combines theoretical knowledge with real-world projects, case studies, and interactive exercises, ensuring learners can effectively apply data science principles in business, research, and technology contexts.
Graduates of this program will be well-prepared for entry-level and mid-level data science roles and will have a strong foundation to pursue advanced certifications or higher studies in analytics, artificial intelligence, and machine learning. The course enhances employability, analytical thinking, and problem-solving capabilities, positioning learners for competitive careers in data-driven industries.
WHAT IS THE MINIMUM GRADE REQUIRED TO DO DIPLOMA IN DATA SCIENCE?
The minimum entry requirement for enrolling in the Diploma in Data Science is a Kenya Certificate of Secondary Education (KCSE) mean grade of C- or equivalent. Applicants should have a background in mathematics and basic computer literacy. Prior knowledge of programming is advantageous but not mandatory.
MODE OF DELIVERY
The Diploma in Data Science is delivered through a flexible online learning model suitable for home or office study.
Learners gain full access to the e-learning platform, interactive discussion forums, practical assignments, and ongoing support from experienced tutors throughout the course duration.
CAREER OPPORTUNITIES
- Data Analyst
- Junior Data Scientist
- Business Intelligence (BI) Analyst
- Data Engineer (Entry-Level)
- Machine Learning Assistant
- Database Analyst
- Research Analyst
- Data Visualization Specialist
- Statistical Analyst
- Reporting Analyst
- Data Operations Associate
- ICT Analyst (Data Focus)
- Cloud Data Associate
PROGRAM GOALS
- Build a strong foundation in statistics, data analysis, and programming.
- Develop practical skills in Python, R, SQL, and other data science tools.
- Strengthen understanding of data visualization, reporting, and dashboards.
- Enhance ability to collect, clean, and preprocess structured and unstructured data.
- Introduce fundamental concepts of machine learning and predictive analytics.
- Foster critical thinking and problem-solving skills in data-driven environments.
- Promote ethical data handling, privacy, and professional practices.
- Prepare learners for data-driven decision-making roles and advanced certifications.
- Cultivate competence in using cloud-based analytics and collaborative data tools.
- Equip learners for careers in diverse sectors including technology, finance, healthcare, and research.
REASONS TO STUDY DIPLOMA IN DATA SCIENCE
- Gain industry-relevant skills aligned with global data science standards.
- Master practical tools and techniques for data analysis and visualization.
- Increase employability in data-driven industries locally and internationally.
- Work on real-world projects and case studies to gain hands-on experience.
- Develop analytical thinking and predictive modeling capabilities.
- Prepare for advanced studies or professional certifications in AI, ML, and data analytics.
- Stay competitive in the rapidly evolving fields of analytics and big data.
- Learn ethical practices in data management and privacy compliance.
- Study at your own pace with flexible online learning.
- Future-proof your career in technology and business intelligence roles.
WHAT WE OFFER
Finstock Evarsity College offers a broad range of programs focused on professional development, job creation, and career advancement. Our courses include online diploma programs, degree programs, freemium courses, and premium learning resources.
All online courses, whether freemium or premium, come with certificates of completion. Learners can register instantly and begin studying at their convenience.
Enroll and study in one of the best online Diploma in Data Science programs globally. Learn from expert tutors, engage in practical exercises, collaborate with peers worldwide, and gain the technical skills and analytical mindset required to thrive in the data-driven era.
TAGS
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Course Instructor(s) for Diploma In Data Science
TBA
Examining Body for Diploma In Data Science
FINSTOCK EVARSITY COLLEGE
FAQs for Diploma In Data Science
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).
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