Full Stack Data Scientist
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.
0 Course instructors
Instructor led course
6 month duration
2 or 6 Month Internship
Course Duration
6 Months of Instructor-led classes with an option of 2 or 6 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
Week 0 - Introduction
The Week 0 - Introduction is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Installations
How to Install Ms Excel
How to Install Tableau
How To Download And Install PostgreSQL
How To Download And Install Anaconda
Module 2: Module 0: Introduction to Data Science
Welcome Address By Efemena
Learning Structure And Roadmap
Stages Of Learning Data Science
What Is Data
Some Basic History
Types Of Analytics
Careers In Data Science
Data Analyst Vs Data Scientist
Data Science Methodology (CRISP-DM)
Module 3: How to Upload Projects on Github
How to create a Portfolio project in Github
Module 4: Portfolio Creation
Portfolio Checklist
Experiencing VScode
Editing the HTML Template
Uploading your portfolio on GitHub Pages
Week 1
Week 1: Excel for Analytics
The Week 1: Excel for Analytics is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 1: Introduction to Excel
Overview of Excel for Data Analytics
Introduction to Microsoft Excel
Cell Referencing
Module 2: 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: 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
Week 2: Excel and Statistics for Analytics - Part 1
The Week 2: Excel and Statistics for Analytics - Part 1 is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 4: Introduction to Statistics and why Statistics
Introduction to Statistics
Statistics (Descriptive and Inferential Statistics)
Module 2: Module 5: Categorical Variable Visualization
Visualization Techniques
Frequency Table
Bar Chart
Pie Chart
Pareto Diagram
Clustered Columns
Summary Tables
Module 3: Module 6: Numerical Variable Visualization
Histogram
Scatter Plot
Box Plot
Module 4: Module 7: Dashboarding
Introduction to Dashboarding
Exercise Intro
Data Analytics
Pivot Tables and Dashboard
Dashboard and Slicers
Week 3
Week 3: Excel and Statistics for Analytics - Part 2
The Week 3: Excel and Statistics for Analytics - Part 2 is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 8: Statistical Concepts
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
Week 4: Forecasting Techniques
The Week 4: Forecasting Techniques is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 9: introduction to Forecasting
Introduction to Forecasting & Predictive Analytics
Types of Forecasting
Quantitative Forecasting
Buzzwords in Forecasting
Forecast Evaluation
Module 2: Module 10: Forecasting Using Excel
Naive Approach
Moving Average
Exponential Smoothing
Simple Linear Regression
Forecast Sheet
Forecast_linear Function
Week 5
Week 5: Tableau for Data Analytics/Science
The Week 5: Tableau for Data Analytics/Science is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 11: Tableau for Data Analytics/Science 1
Introduction to Tableau
Building Blocks of Visualization
Tableau Visualization
Tableau Filters
Time Series Data
Data Prep & Modelling-1
Data Prep & Modelling-2
Week 6
Week 6: Tableau for Data Analytics/Science PRT 2
The Week 6: Tableau for Data Analytics/Science PRT 2 is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 12: Tableau for Data Science 2
Tableau Functions Part 1
Tableau Functions Part 2
Level Of Detail Expression
Formatting- Part 1
Formatting- Part 2
Dashboards In Tableau
Module 2: Module 13: Tableau for Forecasting
Introduction and Calculated Fields
Data Analysis and Visualization 1
Data Analysis and Visualization 2
Forecasting in Tableau
Dashboarding and Stories
Week 7
Week 7: SQL for Analytics
The Week 7: SQL for Analytics is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 14: SQL (Structured Query Language)
Introduction to SQL
Restore your NorthWind Database
SQL Syntax 1
SQL Syntax 2
SQL Syntax 3
SQL Syntax 4 & Save your work
Week 8
Week 8 : SQL Joins & Function
The Week 8 : SQL Joins & Function is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 15: SQL JOINS
Inner Join
LEFT JOIN
RIGHT JOIN 1
RIGHT JOIN 2
FULL JOIN & ALIASES
Module 2: Module 16: SQL Function
Introduction to the Case Study
Download and Extract the Database
Restore the database
CASE & WHEN
COALESCE
CAST
Combining COALESCE, CAST & SUBQUERIES -1
Combining COALESCE, CAST & SUBQUERIES -2
Week 9
Week 9: Python Basics 1 - (Data Types / Structures)
The Week 9: Python Basics 1 - (Data Types / Structures) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 17: Data Types And Structure
Getting Started in Python
Integer and Float
Variable Assignment
Strings
Print formatting
List
Dictionaries
Tuples
Set
Boolean
Bring All Data Types Together
Week 10
Week 10: Python Basics 2
The Week 10: Python Basics 2 is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 18: Conditional Formatting
IF, Elif and Else Statement
And_Or Statement
IF,Elif,Else (and_or)
For Loop
While Loop
Break, Continue and Pass
For Loop (Extra Example)
While Loop (Extra Example)
Function
Function (Extra Examples)
Filter, Map and Lambda Function
Module 2: Module 19: Writing Clean codes with PEP8 guidelines
Introduction to clean coding- Managing Imports
Managing indentation
Utilizing Comments
Documenting with Docstrings
Utilizing blank lines and Managing Line Length
Adhering to Naming Convention and Managing White Space
Week 11
Week 11: NumPy/Pandas and Data Visualization (Matplotlib/Seaborn)
The Week 11: NumPy/Pandas and Data Visualization (Matplotlib/Seaborn) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 20: Numpy
Introduction to Numpy- Vectors, Matrices, Ones, Zeros
Accessing numpy array- Indexing & slicing
Modifying Numpy Arrays- Methods
Functions- sum, min, max, argmax, argmin- Random
Module 2: Module 21: Pandas
Introduction to Pandas
Creating Pandas Series & Dataframes
Basic Pandas Operations- Projecting & Filtering
Joins- Inner, left, Right, Outer
Advanced Dataframe Operations
Slicing & Indexing using Pandas
Week 12
Week 12 - Exploratory Data Analysis
The Week 12 - Exploratory Data Analysis is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 22: Exploratory Data Analysis
Introduction to Case and EDA
EDA 1
Dealing with missing values
Data Analysis
Univariate Analysis
Bivariate Analysis
Multivariate Analysis
Week 13
Week 13: Machine learning (Supervised ML)
The Week 13: Machine learning (Supervised ML) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 23: Intro to Machine Learning
Machine Learning Introduction
What is Machine learning
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Data Pre-Processing
ML Evaluation Techniques
Module 2: Module 24: Supervised ML Project
Peterside Hospital - Case Study Introduction
Python Project Introduction
Univariate Analysis
Bivariate Analysis
Multivariate Analysis
Data pre-Processing
Machine Learning
Machine Learning 2
Week 14
Week 14: Machine learning (Unsupervised ML)
The Week 14: Machine learning (Unsupervised ML) is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 25: Unsupervised ML Project
Selore Nig_Customer Segmentation
Python Project
Week 15
Week 15: Computer Vision
The Week 15: Computer Vision is for both beginner with no experience or experienced professionals, it covers the following modules:
Module 1: Module 26: Face Detection
Computer Vision 1
Computer Vision 2
Computer Vision 3
Computer Vision 4
Computer Vision 5
Module 2: Module 27: Hand Detection
Hand Detection Project
Module 3: Module 28: Pose Detection
Pose Detection
Meet Your Instructor
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
Got a full-time job with Jaguar Land Rover, UK as a Data Engineer after training with 10Alytics on the Full Stack Data Science Program
Idris Adebisi
Got a full-time job as a Regulatory Data Analyst in the UK after training with 10Alytics on the Full Stack Data Science Program
Sunday
Got a full-time job as a Data Scientist in the US after training with 10Alytics on the Full Stack Data Science Program
Nate
Got a full-time job with The NHS, UK as a Data Scientist after training with 10Alytics on the Full Stack Data Science Program
Ebube
Resides in Nigeria and landed a fulltime role as a Data Scientist with Chow420 in the US, after training with 10Alytics on the Full Stack Data Science program.
Abdulrasheed
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.
12-Month Plan
Learners looking for extended industry exposure and advanced skill-building.
6 months of classroom learning + 6 months of internship.
Payment Plan: $125 per month for 8 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.
