Full Stack Data Scientist - 2025
This Full Stack Data Science programme is a comprehensive training designed to equip participants with the skills and knowledge required to excel in the field of data science. Whether you're a beginner or an experienced developer, this programme will help you transition seamlessly into the data science industry by offering hands-on training with popular tools such as Python, Excel, Tableau, and SQL, as well as advanced topics like Machine Learning, Computer Vision, and Natural Language Processing.
3 Course instructors
Instructor led course
8 month duration
2 Month Internship
Course Duration
6 Months of Instructor-led classes with an option of 2 Months Internship
Projects
8 Projects
(20% Discount ongoing - Limited slots)
Program fee payment can be in instalments
Course Description
The Full Stack Data Science (FSDS) program is a comprehensive, hands-on course designed to bridge the gap between theoretical knowledge and real-world application in the field of Data Science. Whether you're a complete beginner with no prior programming experience or an experienced developer looking to transition into Data Science, this program provides all the essential tools and knowledge you need to excel.
Throughout the course, you'll master Python programming, create visually compelling data dashboards, and apply advanced machine learning techniques to solve complex business problems. You’ll be guided step-by-step through key topics such as statistics, data analysis with Excel, interactive visualizations with Tableau, database management with SQL, and Python-based data processing. The program also delves into specialized areas like Machine Learning, Computer Vision, and Natural Language Processing (NLP), ensuring you’re well-equipped to tackle various Data Science challenges.
With 12+ live classes and over 12 portfolio-building projects, you'll gain the confidence and skills to independently analyze data, make data-driven decisions, and present your findings effectively. The 1-month virtual internship further strengthens your hands-on experience, allowing you to apply your knowledge in a professional setting.
Upon completing the course, you’ll be prepared to enter the job market with an impressive portfolio, a deep understanding of data-driven methodologies, and the ability to make an impact in Data Science and related fields.
Course Curriculum
Week 0
Introduction to Data Science
The Introduction to Data Science is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Installation Videos
How to Install Ms Excel
How to Install Tableau
How To Download And Install PostgreSQL
How To Download And Install Anaconda
Module 2: Introduction to Data Science
Welcome Address
Learning Structure And Roadmap
About Facilitators on the LMS
Stages In Learning Data Science
What is Data
Some Basic History
Types of Data
What is Big Data and The 5v’s of Big Data
Types Of Analytics
what is Data science
Data Analysis and Data Analytics
Data Analyst Vs Data Scientist Vs Data Engineer
AI Vs Machine Learning Vs Data Science
Careers In Data Science
Tools in Data Science
Core skills of a Data Scientist
Application of Data Science in various Industries
Data Science Lifecycle
Week 1
Introduction to Excel
The Introduction to Excel is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Introduction to Excel
Overview of Excel for Data Analytics
Introduction to Microsoft Excel
Cell Referencing
Module 2: Data Cleaning Functions Using Excel
Introduction to Data Cleaning in Excel
TRIM Function
CLEAN and Value Function
UPPER, LOWER, PROPER and CONCATENATE
SUBSTITUTE Function
LEFT, RIGHT and SEARCH Function
UNIQUE and Remove Duplicate
Module 3: Data Analyst Toolkit
Data Validation and Conditional Formatting
Referencing, Data Validation and Conditional Formatting
Aggregate Function
Aggregate Function Vs Subtotal
IF, NestedIF and IFS
IF & And, IF & OR and IFERROR
Excel Table, Structured Referencing and COUNTIF
SUMIF(S) and AVERAGEIF(S)
Lookup Functions
Module 4: Extra Materials: Excel Operations
Excel Shortcuts
Paste Special
Move or Copy Data
Hiding and Unhiding Rows/Columns
Freeze Panes
Grouping and Ungrouping Data
Week 2
Introduction to Statistics
The Introduction to Statistics is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Introduction to Statistics and why Statistics
Introduction to Statistics
Statistics (Descriptive and Inferential Statistics)
Module 2: Categorical Variable Visualization
Visualization Techniques
Frequency Table
Bar Chart
Pie Chart
Pareto Diagram
Clustered Columns
Summary Tables
Module 3: Numerical Variable Visualization
Histogram
Scatter Plot
Box Plot
Module 4: Dashboarding
Introduction to Dashboarding
Exercise Intro
Data Analytics
Pivot Tables and Dashboard
Dashboard and Slicers
Week 3
Inferential Statistics & Distribution
The Inferential Statistics & Distribution is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Inferential Statistics & Distribution
Measure of Central Tendency (Mean, Median, Mode)
Dealing with Missing Values
Interquartile Range
Range
Variance and Standard Deviation
Central Limit Theorem
Skewness
Covariance
Correlation
Week 4
Forecasting Techniques
The Forecasting Techniques is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: introduction to Forecasting
Introduction to Forecasting & Predictive Analytics
Types of Forecasting
Quantitative Forecasting
Buzzwords in Forecasting
Forecast Evaluation
Module 2: Forecasting Using Excel
Naive Approach
Moving Average
Exponential Smoothing
Simple Linear Regression
Forecast Sheet
Forecast_linear Function
Module 3: Case Study - Forecasting Techniques
Introduction to project
Naive
Moving Average
Exponential smoothening
linear Regression
Week 5
Tableau Basics, Time Series, Aggregation, and Filters
The Tableau Basics, Time Series, Aggregation, and Filters is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Introduction to Tableau
Week 6
Dashboarding in Tableau
The Dashboarding in Tableau is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Dashboard in Tableau
Week 6
Introduction to SQL
The Introduction to SQL is for both beginner with no experience or experienced professionals, it covers the following modules:
Week 7
SQL For Data Analytics
The SQL For Data Analytics is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: SQL For Data Analytics
Module 2: SQL Functions
Week 8
Python Data Types/Structures
The Python Data Types/Structures is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Python Data Types/Structures
Week 8
Conditional Formatting/ Writing clean code
The Conditional Formatting/ Writing clean code is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Conditional Formatting
Module 2: Writing Clean codes with PEP8 guidelines
Week 9
NumPy/Pandas and Data Visualization (Matplotlib/Seaborn)
The NumPy/Pandas and Data Visualization (Matplotlib/Seaborn) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Numpy
Module 2: Pandas
Week 10
Data Visualization - Matplotlib and Seaborn
The Data Visualization - Matplotlib and Seaborn is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Data Visualization - Matplotlib
Module 2: Data Visualization - Seaborn
Module 3: Exploratory Data Analysis
Module 4: GitHub
Week 11
Machine Learning (supervised and Unsupervised)
The Machine Learning (supervised and Unsupervised) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Machine Learning
Week 12
Unsupervised Learning and Algorithms
The Unsupervised Learning and Algorithms is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Unsupervised Learning and Algorithms
Module 2: Supervised Machine Learning
Module 3: Unsupervised Machine Learning
Week 13
Computer Vision
The Computer Vision is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Image processing using Numpy and OpenCV
Module 2: Hand Detection
Module 3: Pose Detection
Week 14
Extra
The Extra is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Python and SQL
Module 2: Natural Language Processing
Module 3: Recommender Systems
Module 4: ChatGPT For Data Science
Meet Your Instructor
Jedidiah Ayuba Usara
Team Lead Data Science
Jedidiah Ayuba Usara is a Senior Data Associate at 10Alytics with nearly half a decade of experience in data science and analytics. He has worked across industries like finance, healthcare, and aviation in the UK and Canada, contributing to projects in fraud detection, process optimization, and predictive modeling. Jedidiah has trained about a thousand data scientists, equipping them with expertise in tools such as Excel, SQL, Tableau, Python, and Machine Learning. Passionate about sharing knowledge, he is dedicated to empowering others to harness the power of data for innovation and growth.
Daniel Dolapo Orunnaiye
Senior Data Associate
Senior Data Associate
Matthew Oladiran
Facilitator
"Matthew Oladiran is a skilled data analyst with expertise in leveraging data-driven insights to solve complex business challenges. With a strong background in data analysis, machine learning, and predictive modeling, Matthew has contributed to various industries, including technology, energy, and finance. He has a proven track record in creating predictive models, designing interactive dashboards, and leading innovative projects that drive operational efficiency and strategic decision-making. Matthew holds advanced degrees in Data Science and is proficient in Python, SQL, Power BI, and Tableau. His ability to communicate technical insights to diverse stakeholders and lead cross-functional teams ensures successful project outcomes. Matthew has also contributed as a curriculum developer and instructor, empowering others to excel in data science."
Job Opportunities
With our Data Analytics Cerificate, you get to work as any of the following:
Most roles in Data Analytics
Data Scientist
Machine Learning Engineer
Forecasting Analyst
Demand Planning
Big Data Analyst
Quantitative Analyst
Market Research Analyst
NLP developer
Computer Vision Engineer
Course Reviews
Select your preferred pricing plan
As an edu-tech brand, we specialize in providing the essential skills and knowledge you need to unlock high-paying opportunities in the dynamic world of technology. Our mission is simple: to empower individuals to pursue their dreams and excel in high-demand tech roles through intensive, hands-on training.
8-Month Plan
Learners looking for extended industry exposure and advanced skill-building.
6 months of classroom learning + 2 months of internship.
Payment Plan: $150 per month for 5 months.
What You Get:
- Extended internship for in-depth practical experience.
- Access to all advanced course materials and certifications.
- Mentorship and career guidance throughout your journey.
