Training Details

16 weeks
10am to 1pm (Morning)

Weekdays (Mon, Wed, Fri) Weekends (Sat)

1st Floor, Nikky Africana Plaza, 70c Allen Avenue, Obasa Close, Opp UBA, Ikeja, Lagos

Data Science Training In Lagos Nigeria

Our data science training is beginner-friendly, practical and project-based. It is designed to help participants gain mastery of different technologies and tools used to make predictions and classifications using machine learning. It is tailored to help you gain real-world experience that can get you a job and grow your career as a data scientist.

Who should attend

  • Those who are switching career to tech industry.
  • Those planning to travel abroad and seeking hands-on skill that can make them relevant.
  • Those in managerial position seeking to have knowledge of how data is cleaned, analyzed and visualization.
  • Those who studied computer science, mathematics, statistics and other related courses seeking to acquire skill with real-world project to be able to get a job and be relevant to organizations.

Technologies covered

data science training in lagos nigeria

Learning outcomes

Real-World Project

Work on different data such as sales data, customer data, student record, covid-19, customer data, olympic and more

Data science role

Ability to work as a data scientist, data analyst, and engage in data cleaning, prediction, classification and visualization

Version control

Learn how to use online repository like git and GitHub for source code management for collaboration and saving your works

Career Positioning

CV review, interview preparation, LinkedIn profile update, job alert within our alumni community, and mentorship

Course Curriculum

Introduction to data Science

      Introduction and onboarding

  • Introduction to data science
  • Data analytics vs data science
  • Application of data science in real-world
  • What is data?
  • Why data is important
  • Python for data science
  • Understanding data processing
  • Installation of Jupyter notebook

Introduction to Statistics

  • Measures of Central Tendency 
  • Measure of variability 
  • Statistics with Python
  • Measuring Variance
  • Normal Distribution
  • Binomial Distribution
  • Poisson Discrete Distribution
  • Bernoulli Distribution
  • P-value
  • Correlation

Python Programming

Introduction to python

  • What is Python?
  • Installing Python
  • Setting up VSCode for Python
  • Python fundamentals
  • Python Syntax
  • Variables
  • Input and output
  • comments

Data types

  • Strings
  • String properties
  • Indexing and slicing
  • String methods
  • Numbers
  • Boolean

Python lists

  • Introduction to Lists
  • Sorting a List
  • Slicing a List:
  • Unpacking a List
  • Iterating over a List
  • Finding Index of an Element: index()


  • Indexing tuple elements
  • Unpacking Tuples
  • Type Conversion

Python dictionary

  • Introduction to dictionary
  • Nested dictionary
  • Dictionary methods
  • Indexing dictionary items
  • Updating dictionary items
  • Dictionary Comprehension

Python Set

  • Set Comprehension
  • Union of Sets
  • Intersection of Sets
  • Difference between Sets
  • Symmetric Difference of Sets
  • Subset
  • Superset
  • Disjoint Sets


  • Arithmetic Operators
  • Assignment operators
  • Comparison Operators
  • Membership
  • Control flow
  • if…elif
  • type Conversion


  • for Loop
  • while Loop
  • For in loop

Python Functions

  • Inbuilt function
  • User-defined function
  • Default Parameters
  • Keyword Arguments
  • Lambda Expressions
  • Function Docstrings
  • The *args Parameters
  • The **kwargs Parameters
  • Transform List Elements: map()
  • Filtering List Elements: filter()
  • Reducing List Elements: reduce()
  • List Comprehensions

Working with Files

  • Reading a Text File
  • Writing to a Text File
  • Creating a Text File


  • Benefits of using modules
  • Python packages
  • Using the OS module

Personal tasks: Create a function that can process data

Key takeaway: Understand python programming and be able to translate concepts into pseudo-code and program which can be applied to analyze data


Numpy for array manipulation


  • What is Numpy?
  • Array Creation
  • Indexing numpy array
  • Slicing in NumPy
  • Data Type Objects
  • Iterating Over Array
  • Mathematical Function
  • String Operations
  • Sorting, Searching and Counting

Random sampling

  • randint() function
  • random_sample()
  • function
  • ranf() function

Statistical Function

  • Minimum and maximum value
  • Percentile
  • Median
  • Standard deviation
  • Variance
  • Average

Key takeaway: Understand how to work with multi-dimensional array and integrate numpy with other libraries like Pandas and Matplotlib

Pandas for data analytics

Introduction to Pandas

  • Importing pandas libary
  • Creating a Pandas Series
  • Creating a Pandas DataFrame

Pandas Methods

  • Describe and info methods
  • Head and tail method
  • Apply method
  • Unique and nunique method
  • Sorting values
  • Counting values
  • Replacing values
  • Deleting values
  • Largest and lowest values

Manipulating data

  • Dealing with Rows and Columns in Pandas 
  • Extracting rows
  • Indexing and Selecting Data
  • Conditional filtering
  • Handling missing data


Grouping and merging data

  • Grouping data
  • Merging data
  • Joining data
  • Concatenating data
  • Working with date and time
  • Working with text data

Reading files

  • Read CSV files
  • Reading excel file
  • Reading HTML tables from websites

Project: Analyzing covid19 data

Key takeaway: Ability to clean and analyze different types of data

Matplotlib for visualization


  • Overview of Matplotlib
  • Importing matplotlib
  • Plotting your first graph

Adjusting graph

  • Figure Class
  • Axes Class
  • Setting Limits and Tick labels
  • Multiple Plots
  • What is a Legend?


Creating Different Types of Plots

  • Line Graph
  • Bar chart
  • Histograms
  • Scatter Plot
  • Pie Chart
  • 3D Plots
  • Customizing Plots

Project: Grade student results and plot a graph to visualize it.

Takeaway: Being able to plot and style different types of graph

Seaborn for visualization


  • Importing seaborn
  • Using Seaborn with Matplotlib
  • Plotting graph using seaborn

Customizing Seaborn Plots

  • Changing Figure Aesthetic
  • Changing the figure Size
  • Scaling the plots
  • Color Palette
  • Multiple plots with Seaborn

Creating Different Types of Plots

Relational Plots

  • Scatter Plot
  • Line Plot

Categorical Plots

  • Bar Plot
  • Count Plot
  • Box Plot


Distribution Plots

  • Histogram
  • Distplot
  • Pairplot
  • Rugplot

Regression Plots

  • lmplot
  • Regplot

Matrix Plots

  • Heatmap

Key takeaway: Understand how to create and style plots using seaborn

Machine Learning


  • Getting Started with Machine Learning
  • An Introduction to Machine Learning
  • What is Machine Learning?
  • Introduction to Data in Machine Learning
  • Demystifying Machine Learning
  • Applications of Machine Learning
  • Best Python libraries for Machine Learning
  • Difference between Machine learning and Artificial Intelligence

Data and Its Processing:

  • Introduction to Data in Machine Learning
  • Understanding Data Processing
  • Data Cleaning
  • Label Encoding of datasets
  • One Hot Encoding of datasets

Supervised learning :

  • Getting started with Classification
  • Basic Concept of Classification
  • Types of Regression Techniques
  • Classification vs Regression
  • Types of Learning – Supervised Learning
  • Gradient Descent

Linear Regression 

  • Introduction to Linear Regression
  • Application of Linear Regression using sklearn

Logistic Regression

  • Understanding Logistic Regression
  • Why Logistic Regression in Classification?
  • Logistic Regression using Python
  • Naive Bayes Classifiers

Support Vector

  • Support Vector Machines(SVMs) in Python
  • Using SVM to perform classification

Decision tree algorithm

  • Decision Tree Introduction with example
  • Decision Tree Regression using sklearn

Random Forest algorithm

  • Random Forest Regression
  • Application of Random Forest classifier

Unsupervised learning

  • Supervised vs Unsupervised learning
  • Clustering in Machine Learning
  • Different Types of Clustering Algorithms
  • K means Clustering – Introduction
  • Elbow Method for optimal value of k in KMeans
  • K-means++ Algorithm
  • Analysis of test data using K-Means Clustering

Key takeaway: Understanding of how machine learning is used to make predictions and classifications.


Excel for data analysis

  • Introduction
  • Reading CSV, tabbed and fixed column data
  • Data manipulation

Formula basics

  • What is a cell reference?
  • What is a formula?
  • What is a function?
  • How to enter a formula with cell references
  • How to use addition in a formula
  • How to use subtraction in a formula
  • How to use multiplication in a formula
  • How to use division in a formula
  • How to use exponents in a formula
  • The order of operations


  • How to use number formatting in Excel
  • How to use currency formatting in Excel
  • How to use percentage formatting in Excel
  • How to use fraction formatting in Excel

Excel chart

  • How to create a basic chart
  • How to move and resize a chart in Excel
  • How to create a standalone chart
  • How to edit and add to chart data
  • How to add a title and legend to a chart

Working with data and lists

  • How to freeze rows
  • How to quickly sort using one column in Excel
  • How to sort using more than one column
  • How to filter a list
  • How to filter with multiple criteria


  • Relative references
  • Absolute reference
  • Creating a reference to another sheet

Conditional formatting in Excel

  • Using the if function
  • How to create a formula with nested IFs

Working with Text

  • How to join values with an ampersand
  • How to join cell values with concatenating
  • How to clean text with trim
  • How to count characters
  • Changing case in Excel
  • How to extract text

Dates and time

  • How to work with date in excel
  • Formatting date
  • Calculating the number of days
  • Calculating years and months


  • How to use the COUNT function
  • Using the COUNTIF function
  • Using the SUM function
  • How to use SUMIF
  • How to use the AVERAGE function
  • How to calculate the minimum and maximum value
  • How to rank value with the RANK function


  • How to use VLOOKUP
  • How to use VLOOKUP for approximate matches
  • VLOOKUP vs Nested IFs
  • Using the index function
  • Using the match function
  • How to use HLOOKUP

Pivot table

  • What is a pivot table
  • How to create a pivot table
  • How to add fields to pivot tables
  • How to rearrange fields in the pivot table
  • How to adjust aggregate function in pivot table
  • Styling pivot table
  • How to add slicers
  • How to filter pivot table
  • How to sort pivot table
  • How to group pivot table
  • How to create a pivot chart
  • How to change chart type
  • How to work with pivot chart options
  • How to filter pivot chart
  • Pivot chart

Task: Analyzing sales data with excel

Visualizing the data for better
communication with stakeholders using pivot tables and pivot chart

SQL for database manipulation

Introduction to SQL

  • What is SQL?
  • Create Table Statement
  • ALTER TABLE Statements
  • Rename Columns of a Table
  • Modify Column DataType
  • Drop Columns from Table
  • Rename Tables
  • Drop Tables
  • What is Null Value?

DML Statements

  • Insert Statement
  • Update Statement
  • Delete Statement
  • Truncate Statement
  • Merge Statement

SQL Functions

  • AVG()
  • COUNT()
  • MAX()
  • MIN()
  • SUM()

Select Queries

  • Select Query
  • WHERE Clause
  • GROUP BY Clause
  • HAVING Clause
  • ORDER BY Clause
  • SQL Joins

  • Inner Join
  • Left Join
  • Right Join
  • SQL Operators
  • IN
  • LIKE
  • ALL

SQL Operators

  • IN
  • LIKE

Project: Design a database for a social network

Personal task: Design a database for a school management system

Key takeaway: Ability to design and create a database

Implement the database design

Perform CRUD operation

Power BI for Business Intelligence

Introduction to PowerBI

  • What is PowerBI?
  • Installing Power BI
  • Desktop
  • Adjusting Settings in
  • PowerBI

Connecting and shaping data

  • Types of Data Connectors
  • The Power BI Query Editor (Power Query)
  • Basic Table Transformations
  • Working with Numerical Values
  • Working with Date & Time Tools
  • Generating Index & Conditional Columns
  • Grouping & Aggregating Records
  • Merging Queries in
  • Power BI Desktop
  • Appending Queries
  • Configuring Data Source Settings
  • Defining Hierarchies
  • Power BI Data Connection Best Practices

Table relationship and data model

  • What is a “Data Model”?
  • Principles of Database Normalization
  • Understanding Data Tables vs. Lookup Tables
  • Understanding Table
  • Relationships vs. Merged Tables
  • Creating Table Relationships
  • Managing & Editing Table Relationships
  • Connecting Multiple Data Tables
  • Hiding Fields from the
  • Power BI Report View
  • Power BI Data Model Best Practices

Data Analysis Expressions (DAX)

  • Introduction
  • DAX Calculated Columns
  • DAX Measures
  • Adding Columns & DAX Measures
  • Implicit vs. Explicit DAX Measures
  • Filter Context Examples in Power BI
  • Understanding DAX Syntax & Operators
  • Common DAX Function
  • Date & Time Functions
  • Conditional & Logical Functions (IF/AND/OR)
  • Common Text Functions
  • Joining Data with RELATED
  • Basic Math & Stats Functions
  • Iterator Functions (SUMX, RANKX)
  • DAX Best Practices

Data Visualization and report

  • Introduction
  • Exploring the “Report”
  • Adding Simple Objects to the Power BI Report Canvas
  • Inserting Basic Charts & Visuals in Power BI
  • Conditional Formatting
  • Report Formatting Options
  • Report Filtering Options
  • Exploring Data with Matrix Visuals
  • Filtering with Date Slicers
  • Inserting Text Cards
  • Visualizing Geospatial Data with Maps
  • Visualizing Data with Treemaps
  • Artificial Intelligence in PowerBI

Project: Designing of sales dashboard

Key takeaway: Ability to understand how to use PowerBI to learn data, build relationships between tables and create visualization and reports


56 reviews on
Olutosin Oyeleke
Olutosin Oyeleke
Tech365 is the right place to be for acquiring any Tech skill. The teachings are deep, explanatory, and detailed. The teachers take their time to explain each concept and tool from the basics. There is no assumption in their teachings as they take students from beginner level to expert level. Tasks are also given to increase one's knowledge of the scope taught per day. I took Data Analytics and Data Science classes at Tech365, and I can boldly say that I got value for my money. The training centre also provides support and mentorship for their students even after training.
Drastute global Concept
Drastute global Concept
Tech365 is the best for practical experience in teaching for any I.T courses with qualified tutors that are readily available to proved solution to any issues.. I have one certificate from tech365 and I have 2 more to go .I recommend tech365 for anyone with no prior I.T skills to enroll with them.
Francis Ezekude
Francis Ezekude
Tech 365 is an amazing place to upgrade or acquire a tech skill, I definitely recommend it 100%
Chioma Iroka
Chioma Iroka
I didn't allow distance rob me off this amazing experience. One of the best decisions I took this year was, registering at Tech365 for my Data Analysis training. If you need a physical class for your Tech journey, I will advise you go to Tech365. Amazing learning environment, great teachers and hands on projects.
Obateru seun
Obateru seun
It's an amazing experience with Tech365, a great citadel of learning in tech. Learning environment and instructors are top-notch.
Tech365 is the best place to learning. I was taught in a way that even JSS 1 STUDENTS will catch up without losing interest. I will recommend Tech365 to anyone even if you don't have knowledge about IT. TAKE IT FROM ME, it is 100% class and hand-on.
Adebowale Jeff Johnson
Adebowale Jeff Johnson
Class was always fun and very engaging. If you're not comfortable with time management, get yourself together before coming to learn with Tech365.
Oginni Samson
Oginni Samson
I recently attended Tech365 and had an amazing experience! The instructor was knowledgeable, patient, and approachable. He takes him to explain complex concepts in a way that was easy to understand and provided hands-on learning experiences that helped me apply what I learned in real world situations. The curriculum was well-structured and comprehensive, covering a wide range of topics relevant to the tech industry. I appreciated that Tech2365 stayed up-to-date with the latest technology trends, ensuring that students were learning relevant and practical skills that would help them succeed in the workforce. The facilities were top-notch, with modern equipment and plenty of resources available for students. The environment is well organized, and provided a comfortable learning environment. Overall, I highly recommend this tech school to anyone looking to enhance their technical skills or pursue a career in the tech industry. The quality of education and support provided by Tech365 is truly exceptional, and I'm grateful for the opportunity to have learned from such talented and dedicated instructor
mayowa oyeyinka
mayowa oyeyinka
I've been studying Data Science at Tech365 for the past few months and I have to say, it's been an incredibly positive experience. The tutors are knowledgeable and patient, always making sure to answer any questions I have. The classroom environment is also very conducive to learning. What I really appreciate about Tech365 is the resources they provide. They start the classes from scratch, enabling even people without prior experience to catch on. They also organize regular challenges that incorporate hands-on projects into the coursework, which are a great way to put what we've been taught to the test. I would highly recommend Tech365 for anyone looking to move into tech. The knowledgeable instructors and comprehensive resources at Tech365 make it an exceptional place to learn.

Our students work at

Frequently Asked Questions

Yes we accept installment payment. You can discuss with our team members on available payment options.

No prior programming experience is required. However, you need to know how to operate the computer efficiently. Our training approach is beginner friendly, and we work on several real world projects to help our student have deeper understanding of each module. 

People prefer Tech365 because our training are:

  • Project-based training
  • Job recommendation
  • World-class support
  • Up-to-date curriculum
  • Career guidance and mentoring
  • Access to support community
  • Certificate of completion
  • Flexible payment plan
  • Flexible timing


Our training is

  • Globally relevant
  • Beginner friendly
  • Futuristic
  • Relevant across industries
  • In high demand
  • Financially rewarding

We do not guarantee job. However, we do refer our students for jobs as different organization do reach out to us to hire our students. Some of our students have gotten job through this process.

Yes, we offer weekend classes for those who can’t attend weekdays due to their job or other reasons

Our training schedule are around January, May and September. You can talk to one of our representative for more information.

Yes our training is physical at Ikeja, Lagos. However, those outside Nigeria or living far away can join us online via zoom. The experience is similar.

Yes. In fact, this is our strength. We are committed to supporting our students to ensure they succeed.

Yes, it is recommended to come with your own laptop as it will help you to practice whatever you are learning. However, we provide laptop that can be used only within our premises if need be.

Yes, we provide internet access to our students.

Depending on your budget, Core i7, 16 GB ram with SSD is best.

However, core i3 or i5 with 4gb or 8gb ram HDD will also work fine.

It can be HP, DELL, Mac or any other brand.

Our Pricing Plans

Best Data Science/ Training

You can choose available options below based on your need.

Data Science
  • Complete Data Analytics
  • Machine Learning
Artificial Intelligence
  • Complete Data analytics
  • Machine Learning
  • Artificial Intelligence


Tech365 is a register ICT Training company in Lagos Nigeria. Over the years, we have training several students in Canada, UK, United States, Nigeria and more

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