DATA SCIENCE COURSE OVERVIEW 

Data science is the study of data. It involves developing methods for recording, storing, and analyzing data to effectively extract useful information. Data science aims at helping businesses gain insights and knowledge from any type of data - both structured and unstructured data to make predictions and valuable business decisions.

PYTHON FOR DATA SCIENCE

Why we use Python for Data Science?
Python provides a more general approach to data science. Python is better for data
manipulation and repeated tasks. Python is a general-use high-level programming
language that bills itself as powerful, friendly, open, and easy to learn.

PREREQUISITES

• Having a background in mathematics and statistics will be helpful but can be picked up.
• Having an interest in research, performing monotonous tasks, and persistence being persistence is a necessary attribute to excelling in data science.

The course is aimed at helping participants to have 

• Practical data analysis skills that can be applied to practical problems.
• Fundamental knowledge of concepts underlying data science projects and processes.
• Practical skills that are needed in modern-day data analytics.
• Hands-on experience with real-world data analysis.
• Applied experience with data science software, programming, applications, and processes

 DATA ANALYSIS OUTLINE 

• Data Science Overview
• Careers in Data Science
• Real-world application of data Science

Data collection and Data wrangling

• Sources of data
• Data preparation and Pruning
• Data exploration

Python for data science

• Setting up the programming environment
• Understanding the tools and libraries
• Variables, Keywords, and Datatypes
• Input and Output
• Operators
• Data Structures
• Numbers
• Strings
• Lists and list comprehension
• Tuples
• Sets
• Dictionary
• Control Flow
• If, elif, else, statements
• For and while Loop
• Functions and  lambda
• File Handling
• Python Modules
• Hands-on Exercises

Mathematical Computing with Python (numpy)

• Numpy Introduction (ndarray)
• Numpy Overview
• Numerical operations on Numpy
• Basic operations
• Accessing elements
• Slicing
• Exercises

Data Manipulation with Pandas

• Understanding Series
• Understanding DataFrame
• View and Select Data
• Missing Values
• Data Operations
• Indexing, Selection and Filtering
• Dropping entries from an axis
• Concatenation

Data Visualization (Matplotlib and Seaborn)

• Introduction to Matpotlib
• Colors, Markers, and line styles
• Customization of Matplotlib
• Plotting (Barplots, Histograms plots)

Introduction to Seaborn

Introduction to Statistics

Introduction to Probability

Data Exploration

Case Studies

MACHINE LEARNING TRAINING COURSE OUTLINE

Introduction to Machine Learning

• What is Machine Learning?
• Applications of Machine Learning
• Types of Machine Learning algorithm

Feature engineering

Linear Regression 

• Understanding regression
• Used case
• Demonstration of linear regression to predict data

Logistic Regression

• Overview of logistic regression
• Collection of data
• Analyzing the data
• Data wrangling
• Training and test
• Accuracy check

Support Vector Machine (SVM)

Decision tree and Random forest

Data Visualization with Google Data Studio

Real-world Case studies

Certificate of completion 

BENEFITS OF LEARNING DATA SCIENCE

The various benefits of Data Science are as follows:

1. Data Science is greatly in demand.
Prospective job seekers have numerous opportunities. It is the fastest-growing job on Linkedin and is predicted to create 11.5 million jobs by 2026. This makes Data Science a highly employable job sector.

2. Abundance of Positions
There are very few people who have the required skill-set to become a complete Data Scientist. This makes Data Science less saturated as compared with other IT sectors. Therefore, Data Science is a vastly abundant field and has a lot of opportunities. The field of Data Science is high in demand but low in supply of Data Scientists.

3. A Highly Paid Career
Data Science is one of the most highly paid jobs. According to Glassdoor, Data scientists make an average of $116,100 per year. This makes Data Science a highly lucrative career option.

4. Data Science is Versatile
There are numerous applications of Data Science. It is widely used in health-care, banking, consultancy services, and e-commerce industries. Data Science is a very versatile field. Therefore, you will have the opportunity to work in various fields.

5. Data Science Makes Data Better
Companies require skilled Data Scientists to process and analyze their data. They not only analyze the data but also improve its quality. Therefore, Data Science deals with enriching data and making it better for their company.

6. Data Scientists are Highly Prestigious
Data Scientists allow companies to make smarter business decisions. Companies rely on Data Scientists and use their expertise to provide better results to their clients. This gives Data Scientists an important position in the company.

7. No More Boring Tasks
Data Science has helped various industries to automate redundant tasks. Companies are using historical data to train machines in order to perform repetitive tasks. This has simplified the arduous jobs undertaken by humans before.

8. Data Science Makes Products Smarter
Data Science involves the usage of Machine Learning which has enabled industries to create better products tailored specifically for customer experiences. For example, Recommendation Systems used by e-commerce websites provide personalized insights to users based on their historical purchases. This has enabled computers to understand human behaviour and make data-driven decisions.

9. Data Science can Save Lives
Healthcare sector has been greatly improved because of Data Science. With the advent of machine learning, it has been made easier to detect early-stage tumours. Also, many other health-care industries are using Data Science to help their clients.

10. Data Science Can Make You A Better Person
Data Science will not only give you a great career but will also help you in personal growth. You will be able to have a problem-solving attitude. Since many Data Science roles bridge IT and Management, you will be able to enjoy the best of both worlds.

Duration:

Weekdays: 3 times a week (8 weeks

Weekend: Saturdays (16 weeks)

Time: 10am to 1pm

Afternoon: 1pm to 4pm

Venue: EarnIT Tech, Adeniran Oyinlola Avenue, Off Ringroad, Ibadan

Fee:

Data Analysis with Excel = N100,000

(4 weeks)

Data Analysis with python = N200,000

(4 weeks)

Data Science (Full Course) = N300,000

(8 weeks)