The demand for skilled Data Scientists in Kenya is growing fast. This cuts across various industries and domains. To meet this need, Inceptor Institute is offering a Data Science Training Course. This course will equip you with the skills needed to boost your career or improve your business by utilizing the power of data.
The growing amount of data is creating a higher need for data scientists. These experts help businesses, healthcare, and security sectors make smart decisions, innovate, and solve problems using data. In everyday life, you will notice data science applied to recommend movies on platforms like Netflix, predict disease outbreaks, prevent credit card fraud, and optimize services like Uber. It’s all about using data to improve our daily experiences and make informed choices.
Transform yourself into a data science expert in 6 months!
Expert Data Science Training in Nairobi Kenya using Python, R Programming Language or MySQL at Inceptor;Â
Our intensive program offers hands-on training in essential skills like Python, R programming, and MySQL. You’ll learn how to analyze data, create visualizations, and apply machine learning techniques. With practical projects and expert guidance, you’ll gain the knowledge and experience needed to succeed in the rapidly growing field of data science. Don’t miss this opportunity to kickstart your career and become a sought-after data professional!
Here is what you will learn:
- Statistical Analysis and Probability: Learn how to use statistics and probability to analyze data and make informed decisions.
- Machine Learning Algorithms: Understand and apply methods that help predict outcomes, categorize data, and find patterns.
- Data Wrangling and Preprocessing: Clean and prepare raw data to make it easier to analyze.
- Data Visualization: Create charts and graphs to explore data and share key insights clearly.
- Big Data Technologies: Get familiar with tools that help manage and analyze very large amounts of data efficiently.
Data Science Training Course Details
Short Course:
This internal program focuses on 100% practical application in various aspects of Data Science. It also focuses on specific languages. Progress is assessed at key stages, therefore allowing learners to apply knowledge effectively. Additionally learners get to receive valuable feedback. Upon completion, participants should be proficient in executing and demonstrating capabilities in a project.
Our world-class curriculum focus on hands-on practical training relevant to the Kenyan context.
- Data Science Training covers Python, R-Programming, MySQL.
- Duration– 6 Months
- Fees/ cost:Â Ksh 180,000
Prerequisites/ Requirements
- Completion of High School Education
- Basic understanding of IT
- Passion for data handling, programming and problem-solving
The Experience
- Training Model: Hands-On Learning; Gain practical experience with real-world projects.
- Training Mode: In-Person or Online; Choose your preferred learning environment.
- Quality of Training: Expert Instructors; Learn from industry professionals dedicated to your success.
- Comprehensive Curriculum: Tailored to the Kenyan context, integrating practical skills for real-world applications.
Data management and analytics diploma;Â CDACC Program
The course is assessed both internally and externally. Trainers continuously conduct internal assessments, while assessors appointed by TVET CDACC perform external assessments. Successful completion results in a national certificate of competency then issued by TVET CDACC in conjunction with Inceptor Institute of Technology.
Find out more on the CDACC Program Course Here!!
Here is what you will learn:
- Statistical Analysis and Probability: Using statistical methods and probability theory for data analysis and decision-making.
- Machine Learning Algorithms: Understanding and applying various algorithms for predictive modeling, classification, and clustering.
- Data Wrangling and Preprocessing: Cleaning, transforming, and preparing raw data for analysis.
- Data Visualization: Creating effective visualizations to explore and communicate insights from data.
Programming Languages for Data Science
Our main focus will be on:Â Python, R Programming Language and MySQL. The main techniques you will learn in Data Science course consists of cleaning and data organization. Additionally, you will go all the way applying machine learning algorithms. Querying the database and filtering information from relevant fields.
Course Outline
Introduction to Data Science
- Learn how data science is used in different industries.
Overview of Python, R, and MySQL
- Get introduced to popular tools like Python, R, and MySQL for data analysis.
Data Wrangling and Preprocessing
- Learn how to clean and prepare data.
- Handle missing values and outliers.
- Transform and normalize data.
Exploratory Data Analysis (EDA)
- Visualize data using tools like Matplotlib and Seaborn.
- Analyze data trends and relationships between variables.
Statistical Analysis
- Understand basic probability and statistics.
- Perform hypothesis testing and regression analysis.
Machine Learning Basics
- Learn about different machine learning methods like supervised and unsupervised learning.
- Evaluate and validate machine learning models.
Advanced Machine Learning Techniques
- Dive into advanced methods like random forests and deep learning.
Introduction to MySQL Database Management
- Learn how to create and manage databases with SQL.
- Extract and manipulate data using SQL queries.
Integration of Data Science Tools
- Combine Python, R, and MySQL for data analysis.
- Use tools like Jupyter Notebooks for efficient workflows.
Real-world Applications and Case Studies
- See practical examples of data science in action, such as in healthcare or finance.
Skills Application areas:
- Predictive Analytics: Using past data to forecast future events, such as predicting sales, stock market prices, or whether a customer will stop using a service (customer churn).
- Image Recognition: Teaching computers to recognize and categorize images. Useful for diagnosing diseases from medical images, recognizing faces in photos, as well as helping self-driving cars identify objects on the road.
- Natural Language Processing (NLP): Enabling computers to understand and generate human language. Projects include analyzing the sentiment of text (like reviews), then creating chatbots that can converse, or translating languages.
- Recommendation Systems: Suggesting items to users based on their preferences and/ or past behavior. Used for recommending products in online stores, suggesting movies on streaming platforms, or curating content on websites.
- Fraud Detection: Identifying unusual or suspicious activities that may indicate fraud. Examples include spotting fraudulent transactions in banking, detecting misuse of credit cards, and also finding irregular patterns in any system to ensure security.
Grading Criteria:Â The course grading is based on project milestones, offering a hands-on assessment approach. Completing and submitting key project stages will reflect your progress, hence enabling you to apply your knowledge effectively and receive valuable feedback.
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Hazina Towers, 18th floor, Utalii Lane, opposite Anniversary Towers.
Course Features
- Lectures 0
- Quizzes 0
- Duration 24 weeks
- Skill level All levels
- Language English
- Students 0
- Assessments Yes
Requirements
- Successful completion of high school education.
- Knowledge of Coding Basics
Features
- Flexible daytime Morning, Afternoon & Evening Sessions including Weekend Classes.
- Training Model:Â 100% Practical
- Training covers Python, R-Programming, MySQL
