Course Description

Data analysis is the process of evaluating data using analytical and statistical tools to discover useful information and aid in decision making. There are several data analysis methods including data mining, text analytics, business intelligence and data visualization.

Data is everywhere. That means more companies are tracking, analyzing, and using the insights they find to make better decisions. In this course, you’ll learn the fundamentals of data analysis and visualization while building Python skills

This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more.

Who Should Attend

• Data anlysists and Business analysts
• People looking to learn a more powerful software for data analysis
• Anyone interested in learning more about python, data science, or data visualizations.
• Anyone interested about the rapidly expanding world of data science.

Requirements

• Have a computer (either Mac, Windows, or Linux)
• Basic to intermediate knowledge in data management and analysis
• Desire to learn

Duration

5 Days

Learning Outcomes

By the end of this course participants will be able to:

• Import data sets
• Clean and prepare data for analysis
• Know how to use pandas to create and analyze data sets.
• Manipulate pandas DataFrame
• Analyze, Visualize and present data
• Build data pipelines

Course Content

Module I

Importing Datasets

• Understanding the Domain
• Understanding the Dataset
• Python package for data science
• Importing and Exporting Data in Python
• Basic Insights from Datasets
• Getting Started Analyzing Data in Python

Module II

Data Wrangling - Cleaning and Preparing the Data

• Pre-processing data in Python
• Identify and Handle Missing Values in Python
• Data Formatting
• Data Normalization Sets
• Binning in Python
• Indicator variables
• Turning categorical variables into quantitative variables in Python

Module III

Exploratory Data Analysis

• Descriptive Statistics
• GroupBy in Python
• Analysis of Variance - ANOVA
• Correlation
• Correlation - Statistics

Module IV

Model Development

• Simple and Multiple Linear Regression
• Model Evaluation using Visualization
• Polynomial Regression and Pipelines
• R-squared and MSE for In-Sample Evaluation
• Prediction and Decision Making

Module V

Working with Data in Python

• Model Evaluation
• Over Fitting, Under fitting and Model Selection 
• Ridge Regression
• Grid Search 
• Model Refinement

Action Plan

Methodology

The instructor led trainings are delivered using a blended learning approach and comprise of presentations, guided sessions of practical exercise, web based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professionals and trainers in Data Science and programming.

All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.

Accreditation

Upon successful completion of this training, participants will be issued with a certificate of participation.

Training venue

The training is residential and will be held at T4D Training Centre in Westlands Nairobi, Kenya. The course fees cover the course tuition, training materials, two break refreshments, lunch, and study visits.

All participants will additionally cater for their, travel expenses, visa application, insurance, and other personal expenses.

Tailor- made

We can also tailor-make our courses for you. This way, you/your organization will benefit by:

• Using own tools during the training
• Being able to choose areas of interest you wish the trainer to put more emphasis on
• Taking the course in-house or at a venue of choice
• Cutting on the cost of transport and accommodation

For further inquiries, please contact us on details below: 

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Mobile: +254 (0) 729166479

Accommodation

Accommodation is arranged upon request. For reservations contact the Training Officer.

Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Mobile Number: +254 706909947

Training fee

The course fee is KES 75,000.00 or USD 1,100.00 exclusive of VAT. The course fees covers the course tuition, training materials, two (2) break refreshments, lunch and study visits. Participants will cater for their travel and accommodation costs.

Payment

Payment should be transferred to Tech For Development - T4D account through bank on or before the course starting date.

Send proof of payment to This email address is being protected from spambots. You need JavaScript enabled to view it.

Cancellation policy

Payment for the all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

1. Participants may cancel attendance 14 days or more prior to the training commencement date.
2. No refunds will be made 14 days or less to the training commencement date. However, participants who are unable to attend may opt to attend a similar training at a later date, or send a substitute participant provided the participation criteria have been met

Please Note: The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.