List of the best Data Science and Artificial Intelligence Schools/Colleges in Kenya

Given the vast volumes of data created today, data science and artificial intelligence are crucial aspects of many sectors and are one of the most hotly disputed topics in IT circles. Their popularity has expanded over time, and businesses have begun to use data science and AI approaches to expand their operations and improve customer happiness. We’ll discover what data science and artificial intelligence are and how to become a data scientist/AI in this article. Are you thinking about pursuing a career in data science and AI?

What Is Data Science and How Does It Work?

Data science is a field of study that works with large amounts of facts and uses cutting-edge tools and techniques to uncover hidden patterns, extract useful data, and make business decisions. To create prediction models, data scientists use complicated machine learning algorithms.

Data for analysis can come from a variety of sources and be provided in a variety of formats. Now that you know what data science is, let’s look at why it’s so important in today’s IT world.

The Lifecycle of Data Science

The data science lifecycle is divided into five stages, each with its own set of responsibilities:

• Capture

Data Acquisition, Data Entry, Signal Reception, and Data Extraction are all steps in the data capture process. This stage entails gathering unstructured and structured data in its raw form.

• Maintain

Data Warehousing, Data Cleansing, Data Staging, Data Processing, and Data Architecture are all things to keep in mind. This stage entails taking the raw data and converting it into a usable format.

• Process

Data mining, clustering/classification, data modeling, and data summarization are all steps in the process. Data scientists assess the produced data for patterns, ranges, and biases to see if it will be useful in predictive analysis.

• Analyze

Exploratory/Confirmatory, Predictive Analysis, Regression, Text Mining, Qualitative Analysis are some of the methods used to analyze data. This is when the lifespan gets really interesting. This stage entails executing a variety of data analytics.

• Communicate

Data Reporting, Data Visualization, Business Intelligence, and Decision Making are all things that need to be communicated. Analysts present the analyses in clearly legible forms such as charts, graphs, and reports in the last step.

What is the Role of a Data Scientist?

A data scientist examines corporate data in order to derive actionable insights. To put it another way, a data scientist solves business challenges by following a set of procedures, which include:

• The data scientist determines the problem by asking the correct questions and acquiring understanding before beginning data collecting and analysis.

• After that, the data scientist selects the appropriate collection of variables and data sets.
• The data scientist collects organized and unstructured data from a variety of sources, including company data, public data, and so on.

• After the data is acquired, the data scientist analyses it and converts it into an analysis-ready format. Cleaning and validating the data is necessary to ensure uniformity, completeness, and accuracy.
• The data is put into the analytic system—ML algorithm or statistical model—after it has been converted into a usable form. This is where data scientists look for patterns and trends to examine.
• The data scientist evaluates the data once it has been rendered in its entirety in order to uncover possibilities and solutions.
• The data scientists complete the task by producing and communicating the results and insights to the appropriate stakeholders.

What Position Do You Hold in Data Science?

Data science allows you to focus on and specialize in a certain part of the discipline. Here are some examples of how you can get involved in this interesting, fast-growing profession.

• Data Scientist

Determine the problem, the questions that need to be answered, and where the data may be found. They also collect, clean, and present important data.

• Data Analyst

Analysts bridge the gap between data scientists and business analysts by organizing and evaluating data to answer the queries posed by the organization. They convert the technical analyses into qualitative action items.

• Data Engineers

Data engineers are responsible for building, installing, managing, and optimizing the company’s data infrastructure and data pipelines. Engineers assist data scientists by assisting with data transport and transformation in preparation for queries.

Artificial Intelligence.

Artificial intelligence is defined as the process through which machines mimic human intellectual processes, such as natural language processing, machine vision, and speech recognition. Python, Java, and R are the most common programming languages used in artificial intelligence to focus on reasoning, learning, and self-correction skills.

  Artificial Intelligence’s Importance

1. Artificial intelligence does various tasks better than humans in the majority of circumstances.
2. Analyzing a huge number of documents to check that data is appropriately entered
3. Artificial intelligence, which is rapidly improving, has been used in the modern world to improve company processes and gain an advantage over competitors.
4. Produce and deliver consistent outcomes
5. Artificial intelligence works well in tasks that need a lot of attention to detail.
6. Data is processed faster, which saves time.

There are four different types of artificial intelligence.

AI can be divided into four categories, which are as follows:

• Reactive Machines; Reactive machines are task-specific and operate without the use of memory.
• Limited Memory; This sort of artificial intelligence has limited memory for storing information. Self-driving automobiles, for example, are created using this method.
• Theory of mind; This sort of AI aids in the prediction of human behavior and emotions.
• Self-awareness; Artificial intelligence that provides machines self-awareness and consciousness is known as self-awareness.        

List of the best schools offering data science and Artificial Intelligence

1. Janeson Training College
2. Ubunifu college
3. NIIT Kenya
4. Moringa school
5. Kenya School of Monetary Studies.
6. Inceptor Kenya

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