Technology has become the backbone of companies around the world. Among them, data analysis is a critical tool in helping businesses make informed decisions based on proof rather than assumptions. Kenya has a vibrant student culture with a wide range of academic courses, along with extracurricular activities. Students studying in Kenya have access to quality education and a vibrant student campus. In addition, Kenya is a developing country with many emerging industries, which makes studying data analytics courses in Kenya the right choice for students.
Will This Article Be Helpful to You in Helping You Decide About Data Analytics Courses in Kenya?
The answer is a definite yes. This article is going to help you in understanding all the aspects of data analytics. How it is used? Where it is used? And what are the benefits involving it? And also the article will help you to opt for the various data analytics courses in Kenya, which will help you progress in your career.
The Contents of the Article:
- What exactly is Data Analytics?
- What are the advantages of Data Analytics?
- The sectors where Data Analytics are being applied.
- The various Data Analytics Courses in Kenya.
What is Data Analytics?
Data Analytics is a process of analyzing and deciphering massive amounts of data to find patterns, relationships, and trends in the business market. In order to extract insights and useful information from data that can be used to make informed business decisions, data analysis involves using statistical and computational techniques.
Various industries use data analytics to examine data and derive insights that can guide strategic decision-making. Data analytics are frequently used for the following purposes:
- Business analysis: Data analytics is used to track key performance indicators (KPIs) and to learn about customer behavior, market trends, and business operations. Strategic decision-making and enhanced business performance are both assisted by this data.
- Marketing: By recognizing customer behavior patterns and preferences using data analytics, businesses are able to develop more specialized and successful marketing campaigns.
- Healthcare: To assess patient data and significantly improve patient outcomes, data analytics is used. It is used to determine risk factors, forecast the course of the disease, and guide treatment strategies.
- Finance: Financial data is analyzed using data analytics to find trends and irregularities. It is applied to manage risk, make informed investment decisions, and enhance financial performance.
- Operations: Data analytics is used to optimize cost-effectiveness, production efficiency, and supply chain management.
Overall data analysis is used across many sectors, enabling businesses to gather the information that helps them make strategic decisions, perform better, and accomplish their objectives.
What Are the Advantages of Data Analytics Courses in Kenya?
- High Demand for Data Analysts: As more and more businesses recognize the value of data-driven decision-making, there has been a sharp rise in demand for data analysts in Kenya in recent years. By taking data analytics courses in Kenya, you can position yourself for a career in this high-demand field.
- Competitive Job Market: Kenya’s job market is extremely competitive, so having knowledge of data analytics can give you an advantage over other job applicants. Employers usually are willing to pay more for professionals who have specialized skills, like data analytics.
- Access to Cutting-Edge Technology: Many data analytics programs in Kenya make use of cutting-edge hardware and software, allowing you to get first-hand experience with the instruments and procedures employed in the industry. This experience may be helpful in advancing your career and finding new employment opportunities.
- Opportunities for networking: Enrolling in data analytics courses can give you the chance to connect with other industry experts, which can be essential for progressing your career.
- Personal and Professional Development: Gaining knowledge of data analytics can help you improve your ability to think critically, solve problems, and gain a deeper understanding of data and statistics. These abilities will help you become a more well-rounded person because you can use them both in your professional and personal lives.
Overall, enrolling in data analytics courses in Kenya can be a wise career move, giving you the knowledge and abilities required to succeed in this quickly expanding industry.
Sectors That Make Use of Data Analytics
They use data analysis in many sectors, that include:
- Business: Organizations use the data tool to understand managing their supply chains, analyze consumer behavior, and make data-driven decisions that lead to higher profits.
- Healthcare: Healthcare providers use data analytics to monitor patient health, expect disease outbreaks, enhance patient outcomes, and lower healthcare costs.
- Finance: To identify fraud, evaluate credit risk, assess market trends, and enhance investment decisions, financial institutions use data analytics.
- Education: Educational institutions use data analytics to track student progress, identify problem areas among students, and create individualized learning plans for them.
- Government: Governments monitor social and economic trends, enhance public services, and develop data-driven policy decisions through data analysis.
- Sports: To analyze player performance, optimize training schedules and achieve a competitive edge, sports teams use data analytics.
- Transportation: Transportation companies are looking for ways to optimize routes to be taken, lowering fuel consumption and the safety of people using transportation through data analytics.
Recommended Read: Financial Modeling Courses in Kenya
Now Let Us Take a Look at the Various Data Analytics Courses One Can Opt for in Kenya
1. Data Analytics Courses in Kenya: KnowledgeHut
KnowledgeHut is a leading training provider that aims at providing world-class training through a practical and innovative approach.
Name of the Course: Big Data Analytics Course Training
Depending on the mode of teaching, it is divided as-
- Online training: Duration of 15 sessions. 2 hours per day.
- Weekend training: Duration of 5 Weekends. They hold a class 2 days per week on Saturday and Sunday. Each session of 3 hours.
Mode of Teaching: It is conducted in three ways-The course is conducted in three ways-
- Online classroom instruction: Using the most popular virtual, live, and interactive training, you can learn from anywhere.
- Self-paced learning: With this method of instruction, you will have lifetime access to premium, self-paced e-learning resources created by our team of industry experts.
- Team/Corporate Training: For this kind of training, a business can choose a single employee or an entire team to participate in the online or in-person training. The extra features of this training include a standard Learning Management System (LMS), an enterprise dashboard, and flexible pricing options. Additionally, you can alter the curriculum to suit your learning requirements and receive post-training assistance from the expert during the execution of a real-world project.
Fee Structure: Not available.
- Introducing Big Data and Hadoop
Objective: Big data problems in the real world will be introduced to you, and you’ll learn how to use cutting-edge tools to solve them. Recognize how Hadoop’s exceptional features provide alternatives to conventional processing. You will learn about the history of Hadoop and the various commercial Hadoop distributions. The Unix Box is therefore ready for the training.
Hands-on: VMPlayer is used to install a virtual machine on the host computer. And practice some fundamental Unix commands that Hadoop requires.
- Hadoop Daemon Process
Objective: You will gain a thorough understanding of the various Daemons and how they operate.
- Name Node
- Data Node
- Secondary Name Node
- Job Tracker
- Task Tracker
1. Makes a Unix Shell Script that will run each daemon at once.
2. Launch HDFS and MR independently.
- HDFS (Hadoop distributed file system)
Objective: You will learn how to read and write files in HDFS. Recognize the functions of the Name Node, Data Node, and Secondary Name Node in the HDFS Architecture. Additionally, you will be aware of various HDFS data access methods.
- Blocks and Input Splits
- Data Replication
- Hadoop Rack Awareness
- Cluster Architecture and Block Placement
- Accessing HDFS
- JAVA Approach
- CLI Approach
- Creates a shell script that can write to and read from HDFS files.
- The replication factor is altered on three levels.
- Use Java when working with HDFS.
- Writes various HDFS commands as well as administrative commands.
- Hadoop installation modes and HDFS
- You will become familiar with the various Hadoop modes, gain a thorough understanding of the P configuration and work with Configuration.
- You will gain knowledge of the functionality of various HDFS operations and visually represent HDFS read and write actions along with their Daemons Namenode and Data Node.
- Local Mode
- Pseudo-distributed Mode
- Fully distributed mode
- Pseudo Mode installation and configurations
- HDFS basic file operations
Hands-on: Set up the VirtualBox Manager and set up Hadoop in pseudo-distributed mode. Alterations to the various configuration files are necessary for pseudo-distributed mode. undertake various file operations on HDFS.
- Hadoop Developer Tasks
- Recognize the varied Map Reduce phases, including the Map, Shuffling, Sorting, and Reduce phases.
- Get a thorough understanding of the MR life cycle before submitting it to YARN.
- Find out more about the Distributed Cache concept with examples.
- Create a Wordcount MR program, then use Job Tracker and YARN Console to keep a watch on the job. Also, explore additional use cases.
- Basic API Concepts
- The Driver Class
- The Mapper Class
- The Reducer Class
- The Combiner Class
- The Partitioner Class
- Examining a Sample MapReduce Program with several examples
- Hadoop’s Streaming API
- Discover how to create MR jobs from scratch, create various Mapper and Reducer logics, and submit MR jobs in Standalone and Distributed modes.
- Learn how to write MR jobs with a word count, calculate an employee’s average salary if they meet certain criteria, and use MR to calculate sales.
- Hadoop Ecosystems: This concept is explained by dividing it into six parts.
- Part 1- PIG
- PIG concepts
- Install and configure PIG on a cluster
- PIG Vs MapReduce and SQL
- Write sample PIG Latin scripts
- Modes of running PIG
- PIG UDFs.
Part 2- HIVE
- Hive concepts
- Hive architecture
- Installing and configuring HIVE
- Managed tables and external tables
- Joins in HIVE
- Various ways of including data in HIVE tables
- CTAS, views, alter tables
- User-defined functions in HIVE
- Hive UDF
Part 3- SQOOP
- SQOOP concepts
- SQOOP architecture
- Install and configure SQOOP
- Connecting to RDBMS
- Internal mechanism of import/export
- Import data from Oracle/MySQL to HIVE
- Export data to Oracle/MySQL
- Other SQOOP commands.
Part 4- HBASE
- HBASE concepts
- ZOOKEEPER concepts
- HBASE and Region server architecture
- File storage architecture
- NoSQL vs SQL
- Defining Schema and basic operations
- HBASE use cases
Part 5- OOZIE
- OOZIE concepts
- OOZIE architecture
- Workflow engine
- Job coordinator
- Installing and configuring OOZIE
- HPDL and XML for creating Workflows
- Nodes in OOZIE
- Action nodes and Control nodes
- Using the web console and the CLI to access OOZIE jobs
- Develop and run sample workflows in OOZIE
- Run MapReduce programs
- Run HIVE scripts/jobs.
Part 6- FLUME
- FLUME Concepts
- FLUME Architecture
- Installation and configurations
- Executing FLUME jobs
- Using Pentaho as an ETL tool for data analytics
- Data Analytics using Pentaho as an ETL tool
- Big Data Integration with Zero Coding Required
Hands-on: You will use learn to use Pentaho as an ETL tool for data analytics.
- MapReduce and HIVE integration
- MapReduce and HBase integration
- Java and HIVE integration
- HIVE – HBASE Integration
Hands-on: Integrates HIVE and HBASE using storage handlers. Also incorporates HIVE and PIG.
Projects students will work on:
● Recommendation Engine
● Sentimental Analytics
● Clickstream Analytics
What will you experience at KNOWLEDGEHUT
- INSTRUCTOR-LED LIVE CLASSROOM
- CURRICULUM DESIGNED BY EXPERTS
- LEARN THROUGH DOING
- MENTORED BY INDUSTRY LEADERS
- ADVANCE FROM THE BASICS
- CODE REVIEWS BY PROFESSIONALS
2. Data Analytics Courses in Kenya- Simplilearn
Founded in 2010, Simplilearn is a leader in providing online boot camps in digital skills. Here they have partnered with Purdue University, Nairobi in collaboration with IBM to provide a Data Analytics course to expand your skill set, thereby increasing your career potential.
Course Name: Post-Graduate Program In Data Analytics, Nairobi.
Course Duration: 8 months.
Fee Structure: $ 2,140. EMI starting from- $178.33/mo.
Mode of Teaching: Online boot camp.
- Induction program for Purdue data analytics program.
- PC DA- Analytics foundation.
- PC DA- Python foundational programming and data analysis.
- PC DA- R programming for data science.
- PC DA- Data Science with R.
- PC DA- Tableau training.
- PC DA- Data analyst capstone.
- Power BI.
- Introduction to artificial intelligence.
- Master class- Purdue University.
- Industry master class- Data analytics.
What are the skills covered?
- Data Analytics
- Statistical Analysis using Excel.
- Data Analysis Python and R.
- Data Visualization Tableau and Power BI.
- Linear and logistic regression modules.
- Clustering using kmeans.
- Supervised Learning.
Tools taught in the program:
- Microsoft Excel.
- Power BI.
- Scikit Learn.
Industry-related projects :
- Project 1- Predicting the ratings for apps on the Google Play store.
- Project 2- Forecasting demand for Walmart.
- Project 3- IBM’s attrition modeling.
Who is eligible to take up this course?
- A minimum average of 50% in bachelor’s degree.
- Prior professional experience is optional.
- Both programming and non-programming students are welcome.
Key advantages of choosing data analytics courses in Kenya from Simplilearn:
- Get a Professional Program certificate and membership in the Alumni Association.
- Extensive hackathons and question and answer sessions by IBM.
- Almost 8 times more live interaction in live online classes by industry experts.
- Capstone from three different fields and 14+ data analytics projects with industry datasets from Lyft, the World Bank, Google Play, and other sources.
- Master classes conducted by Purdue faculty and IBM experts.
- A joint Purdue- Simplilearn program certificate.
Call us – 1800-212-7688.
- Data Analytics Courses in Germany
- Data Analytics Courses in Zurich
- Data Analytics Courses in Dubai
- Data Analytics Courses in London
- Data Analytics Courses in Nigeria
- Data Analytics Courses in the UK
3. Data Analytics Courses in Kenya- EXCELR
Not interested in coding? Not to worry, this data analytics course from EXCELR is your perfect option to upgrade your career graph without learning to code.
Course Name: Analytics/ Data Analytics certification training course in Kenya.
Course Duration: 6 months.
Fee Structure: $ 950.
- Data Analyst + Data Science- $1400.
- Data Analyst + AWS- $ 1150.
- Data Science + Data Analyst + AWS- $ 1800.
- Data Analyst + Core Python- $ 875.
Mode of teaching: Live online classroom.
- Business statistics.
- EXCEL- Basics to advanced.
- Power BI.
- R basics.
- Python basics.
Advantages of opting for a data analytics course with EXCELR
- The curriculum is designed so that students who have no prior experience with data analysis can easily master the concepts.
- The faculties at EXCELR are the best in the industry.
- Chances to work on numerous projects from various industries. The students can choose the projects according to their interests.
- Access to the recorded sessions.
- 50+ assignments with 100 hours of theoretical practice to master the concepts.
- Assistance with job placement including resume building and mock interviews.
Contact: Ph- 18002122121
4. Data Analytics courses in Kenya- @iLabAfrica
The Faculty of Information Technology at Strathmore University established the @iLabAfrica Center of Excellence in ICT Innovation and Development in 2011. This course provides an overview of the fundamental principles and concepts of Data Analytics through the use of effective, user-friendly ICT tools.
Course Name: Data Analytics training.
Course Duration: 2 days course.
Fee Structure: KSh 45,000 per participant.
Mode of teaching: Classroom. The training is conducted at @ilabAfrica Research Center, Strathmore University.
Program format: They combine both theory and practice in the program. Since it is a very practical course, it is conducted in a computer lab, and each student is given a workstation with the necessary software installed. In the practical sessions, case-based group and individual assignments require pulling data from various sources, analyzing that data, and creating visualizations.
Advantages of opting for a course at @ilabAfrica Research Center
- Understanding of Data-Analysis.
- Learning how to get and prepare data with the user of ICT tools.
- A manual for creating meaningful and engaging visuals that tell impactful stories hidden in data.
- A practical session on how to use select data analytics ICT tools like charts and Qlik sense.
- Each participant receives a certificate of participation after successfully completing the course.
Prerequisites to opt for this course?
- Basic computer operating skills.
- Familiar with the use of spreadsheets.
Contact: Ph- +254 703 034616
5. Data Analytics Courses in Kenya- Bachelor of Science in Data Science and Analytics – United States International University – Africa
The primary goal of the Data Science and Analytics program is to produce graduates with specialized training who possess the fundamental computer science and mathematics knowledge and abilities required to present, examine, and ultimately comprehend data sets.
Course Name: Analytics and data science bachelor’s degree.
Course Duration: 40 months.
Fee Structure: INR 939,085
Mode of Teaching: On-campus.
Modules of Data Analytics Courses in Kenya:
Lower division courses- 54 units.
- Probability and Statistics
- Linear Algebra
- Differential equations
- Analytical and Computational Foundation
- Introduction to Programming
- Database systems
- Introduction to Data Science
- Discrete Mathematics for Data Science
- Optimization Techniques
- Numerical Analysis and Its application
- Probability & Statistics II
- Statistical Inference
- Programming with R for Data Science
- Sample Surveys
- Principles of Machine Learning
- Data Structures and Algorithms
- Data Mining and Analytics
Upper-division courses- 57 units
- Introduction to Artificial Intelligence
- Statistical Modeling
- Designs and Analysis of Experiments
- Mathematical Modeling and Simulation
- Bayesian inference and Decision
- Mathematical Finance
- Object Oriented Programming
- Big Data Analytics
- Knowledge-based Systems
- Big Data Security
- Applied Machine Learning
- Advanced Programming for Data Science
- Applied Project in Data Science
- Survival Analysis
- Applied Multivariate Statistical Analysis
The objective of the course:
- Use sound data science principles to solve analytical problems
- Create analytical models, then highlight their strengths and weaknesses.
- Utilize computational and programming tools to analyze and display data sets.
- Use computer algorithms for data mining.
- Apply data science techniques.
Ph: +254 730 116 000 /290 /291
Frequently Asked Questions About Data Analytics Courses in Kenya
1. What are a data analyst’s tasks and responsibilities?
Once you have successfully completed the course in data analysis you will be responsible for –
- Data collection and extraction
- Data cleaning and preparation
- Data analysis
- Data modeling
- Communication and reporting
- Continuous improvement.
2. What is the job scenario in the field of Data Analysis in Kenya?
Kenya has a growing need for qualified professionals in the field of data analytics. Kenyan businesses in the financial, healthcare, telecommunications, e-commerce, and government sectors are among those that are hiring data analysts.
The demand for data analysts in Kenya may vary depending on the industry, company size, and level of experience, as it does in any job market. However, there are numerous job openings in Kenya for data analysts, and the industry is predicted to expand even more in the years to come.
3. How much does a Data Analyst working in Kenya earn?
The average annual salary for a data analyst in Kenya is KSh 621,243, according to PayScale. While experienced professionals can make up to KSh 2,000,000 or more per year, entry-level positions may start at around KSh 300,000. It’s important to remember that location can have an impact on salaries as well, with data analysts in bigger cities like Nairobi possibly earning more money than those in smaller communities.
4. Can a non-programmer learn Data Analysis?
Definitely, a non-programmer can take up a course in Data Analysis and work as a Data Analyst. Tools like Microsoft Excel, Google Sheets, or Tableau are used by data analysts to analyze data without coding. In addition, there are numerous paid and free online data analytics courses in Kenya that teach data analysis methods and tools, including SQL, R, and Python, which can assist non-programmers in learning the abilities required to conduct data analysis. The most important part is to have a firm grasp of statistical ideas and procedures as well as a readiness to study and work with data.
For those wanting to pursue a career in Data Analysis, the various data analytics courses in Kenya discussed in this article will give you a clear picture. Courses that are uniquely designed, including online and in-person training, whether you are a beginner or an experienced professional.Will help you learn important skills and knowledge that will enable you to effectively manipulate and interpret large amounts of data by enrolling in a data analytics course.
A career in data analytics offers excellent opportunities for growth and advancement due to the growing use of data in decision-making processes. Therefore, anyone with an interest in this area can look into the programs that are offered and take the first step toward a lucrative career in data analytics.