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Data Analysis Bootcamp

Learn Data analysis to drive insights, innovation, and informed decisions in modern business and society.

Bahati Remote Solutions Data Analysis BootCamp in Kenya

Course Description & Overview

Data analysis involves inspecting, cleaning, transforming, and modeling data to uncover useful insights and inform decision-making. It's about extracting meaningful information from raw data to drive informed actions and strategies.

Program Overview

Excel Fundamentals

In this module, you'll master Excel's key functions like data manipulation, formulas, and organization. With interactive sessions and hands-on exercises, you'll become proficient in using Excel for powerful data analysis.

Data Visualization with Tableau

You will explore data visualization with Tableau, a top industry software. From basic charts to advanced dashboards, students will learn to turn raw data into compelling visual insights for informed decisions.

Python Part 1

This module covers Python fundamentals for data analysis, including variables, data types, control structures, and functions. Through hands-on exercises, students will gain a solid foundation in Python programming.

Python Part 2

This module expands on Python Part 1 with advanced topics like data manipulation, visualization libraries (e.g., Matplotlib, Seaborn), and external data sources. Participants will work on real-world projects to strengthen their data analysis skills in Python.

Database Management with PostgreSQL

In this module, students will master relational database management with PostgreSQL. From designing databases to querying data using SQL, participants will gain the skills to efficiently manage and analyze large datasets.

Project-Based Learning and Portfolio Creation

During the bootcamp, participants will tackle real-world projects mirroring industry scenarios, applying their skills in practical settings. These projects will result in a comprehensive portfolio highlighting participants' abilities and achievements in data analysis.

Upgrade Your Data Analysis Skills Now

Master data analysis techniques for a fulfilling career with limitless growth potential and impact.

Financing Options

Full Payment

  • Pay the full tuition fee of Ksh. 80,000 upfront at the beginning of the bootcamp.

Two Monthly Installments

  • Pay Ksh. 40,000 at the start of the bootcamp and another Ksh. 40,000 at the start of the third month.

Four Monthly Installments

  • Make four equal payments of Ksh. 20,000 each, spread over four months.

Study per Module

  • Kindly reach out to us for more information on this package

Benefits of Financing Options

Join Bahati Remote Solutions Data Analysis Bootcamp today and embark on a journey towards becoming a proficient data analyst!

  • Flexibility: Our financing options allow participants to choose a payment plan that best fits their financial situation.
  • Accessibility: By offering instalment plans, we aim to make the bootcamp accessible to a wider range of individuals who may prefer to manage their expenses over time.
  • No Hidden Fees: There are no additional fees or interest charges associated with our instalment plans. Participants only pay the agreed-upon tuition amount.

Key Components of Data Analysis

  1. Data Collection: - Data analysis begins with the collection of relevant data from various sources. This could include structured data from databases, unstructured data from text documents or social media, or even sensor data from Internet of Things (IoT) devices.
  2. Data Cleaning and Preparation: - Raw data often contains errors, inconsistencies, or missing values, which can hinder analysis. Data cleaning involves identifying and rectifying these issues to ensure the accuracy and completeness of the data. Additionally, data may need to be transformed or formatted for analysis.
  3. Exploratory Data Analysis (EDA): - EDA involves examining the data to understand its underlying patterns, distributions, and relationships. This phase often includes techniques such as summary statistics, data visualization, and correlation analysis to gain insights into the data's structure and characteristics.
  4. Statistical Analysis: - Statistical analysis involves applying statistical methods and techniques to quantify relationships within the data, test hypotheses, and make predictions. This may include descriptive statistics, inferential statistics, regression analysis, and hypothesis testing.
  5. Data Visualization: - Data visualization is the process of representing data visually through charts, graphs, and interactive dashboards. Visualizations help to communicate insights more effectively, enabling stakeholders to grasp complex patterns and trends at a glance.
  6. Machine Learning and Predictive Modeling: - Machine learning techniques are used to build predictive models that can identify patterns and make predictions based on historical data. These models can be applied to tasks such as classification, regression, clustering, and recommendation systems.
  7. Interpretation and Decision-Making: - The final stage of data analysis involves interpreting the findings and using them to inform decision-making processes. This may involve presenting insights to stakeholders, identifying actionable recommendations, and iterating on analysis based on feedback and new data.

Start your journey towards becoming a proficient data analyst with Bahati Remote Solutions today!