Data Analytics course in Pakistan
Join the most in-demand Data Analytics course in Pakistan and gain job-ready skills with hands-on training in Python, Excel, Power BI & more.
Enrolment
Click on Start Making Money to register for the program
Program Duration
5 months
Learning Format
Online
What You Will Learn
- Gain an immersive understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job
- Learn key analytical skills (data cleaning, analysis, & visualization) and tools (spreadsheets, SQL, R programming, Tableau)
- Understand how to clean and organize data for analysis, and complete analysis and calculations using spreadsheets, SQL and R programming
- Learn how to visualize and present data findings in dashboards, presentations and commonly used visualization platforms
Course Syllabus
Module 1
Module 2
Module 3
Module 4
Module 1
- SQL Fundamentals and Database Overview
- Basic Data Retrieval and Filtering
- Data Modification and Management (DML)
- Aggregate Functions and Grouping Advanced
- Aggregations and Window Functions
Module 2
- Data Relationships and Joins
- Subqueries and Common Table Expressions (CTEs)
- Set Operations and Conditional Logic
- Data Warehousing Concepts and Data Transformation
- Power BI Integration and Visualization
Module 3
- Python Basics for Data Analysis
- Data Cleaning and Preprocessing
- Exploratory Data Analysis (EDA) and Visualization
- Advanced Data Manipulation and SQL in Python
Module 4
- Feature Engineering and Transformation
- Time-Series Forecasting and Predictive Analysis
- Data Warehousing and Data Mart Design in Python
- Visualizations
- SQL Fundamentals and Database Overview
- Basic Data Retrieval and Filtering
- Data Modification and Management (DML)
- Aggregate Functions and Grouping Advanced
- Aggregations and Window Functions
- Data Relationships and Joins
- Subqueries and Common Table Expressions (CTEs)
- Set Operations and Conditional Logic
- Data Warehousing Concepts and Data Transformation
- Power BI Integration and Visualization
- Python Basics for Data Analysis
- Data Cleaning and Preprocessing
- Exploratory Data Analysis (EDA) and Visualization
- Advanced Data Manipulation and SQL in Python
- Feature Engineering and Transformation
- Time-Series Forecasting and Predictive Analysis
- Data Warehousing and Data Mart Design in Python
- Visualizations
Program Offerings
Practical Skills
You will learn practical skills in emerging careers that make you more valuable and appealing to employers
Projects
You will acquire the knowledge to create portfolio-worthy projects showcasing your skills
Mentorship
Seasoned professionals will provide support to navigate career paths and focus on skills development.
Certification
Earn an Industry-Recognized Certificate
Complete our program and receive a professional certificate to showcase your skills.
Add it to your LinkedIn profile, resume, or CV to highlight your commitment to growth and stand out in the job market.
Module 7
- Week 9
Clean Data, Assignment Prep
Module 8
- Week 10
Cleaning Data with SQL, Verify and Report Cleaning Results
Module 9
- Week 11
Adding Data to Resume + Course Challenge
Module 10
- Week 12
Organizing Data to Begin Analysis, Formatting and Adjusting Data
Module 11
- Week 13
Aggregating Data for Analysis, Performing Data Calculations
Module 12
- Week 14
Visualizing Data, Creating Data Visualizations with Tableau
Module 13
- Week 15
Crafting Data Stories, Developing Presentations and Slideshows
Module 14
- Week 16
Programming and Data Analytics, Programming using R Studio
Module 15
- Week 17
Working with Data in R, More About Visualizations, Aesthetics and Annotations
Module 16
- Week 18
Documentation and Reports, Learn About Capstone Basics
Module 17
- Week 19
Building Your Portfolio + Using Your Portfolioo
Module 18
- Weeks 20 & 21
Putting Your Certificate to Work
Module 19
- Weeks 22 & 23
Introduction to Probability and Data with R
Module 20
- Weeks 24 & 25
Inferential Statistics
Module 21
- Weeks 26 & 27
Linear Regression and Modelling
Module 22
- Weeks 28 & 29
Bayesian Statistics
Module 23
- Weeks 30
Statistics with R Capstone (Final Project)
Module 24
- Weeks 31
Job - Interview Mocking and Training
Module 7
- Week 9
Clean Data, Assignment Prep
Module 8
- Week 10
Cleaning Data with SQL, Verify and Report Cleaning Results
Module 9
- Week 11
Adding Data to Resume + Course Challenge
Module 10
- Week 12
Organizing Data to Begin Analysis, Formatting and Adjusting Data
Module 11
- Week 13
Aggregating Data for Analysis, Performing Data Calculations
Module 12
- Week 14
Visualizing Data, Creating Data Visualizations with Tableau
Module 13
- Week 15
Crafting Data Stories, Developing Presentations and Slideshows
Module 14
- Week 16
Programming and Data Analytics, Programming using R Studio
Module 15
- Week 17
Working with Data in R, More About Visualizations, Aesthetics and Annotations
Module 16
- Week 18
Documentation and Reports, Learn About Capstone Basics
Module 17
- Week 19
Building Your Portfolio + Using Your Portfolioo
Module 18
- Weeks 20 & 21
Putting Your Certificate to Work
Module 19
- Weeks 22 & 23
Introduction to Probability and Data with R
Module 20
- Weeks 24 & 25
Inferential Statistics
Module 21
- Weeks 26 & 27
Linear Regression and Modelling
Module 22
- Weeks 28 & 29
Bayesian Statistics
Module 23
- Weeks 30
Statistics with R Capstone (Final Project)
Module 24
- Weeks 31
Job - Interview Mocking and Training
Module 7
- Week 9
Clean Data, Assignment Prep
Module 8
- Week 10
Cleaning Data with SQL, Verify and Report Cleaning Results
Module 9
- Week 11
Adding Data to Resume + Course Challenge
Module 10
- Week 12
Organizing Data to Begin Analysis, Formatting and Adjusting Data
Module 11
- Week 13
Aggregating Data for Analysis, Performing Data Calculations
Module 12
- Week 14
Visualizing Data, Creating Data Visualizations with Tableau
Module 13
- Week 15
Crafting Data Stories, Developing Presentations and Slideshows
Module 14
- Week 16
Programming and Data Analytics, Programming using R Studio
Module 15
- Week 17
Working with Data in R, More About Visualizations, Aesthetics and Annotations
Module 16
- Week 18
Documentation and Reports, Learn About Capstone Basics
Module 17
- Week 19
Building Your Portfolio + Using Your Portfolioo
Module 18
- Weeks 20 & 21
Putting Your Certificate to Work
Module 19
- Weeks 22 & 23
Introduction to Probability and Data with R
Module 20
- Weeks 24 & 25
Inferential Statistics
Module 21
- Weeks 26 & 27
Linear Regression and Modelling
Module 22
- Weeks 28 & 29
Bayesian Statistics
Module 23
- Weeks 30
Statistics with R Capstone (Final Project)
Module 24
- Weeks 31
Job - Interview Mocking and Training
Instructors
Umair Rafique
Umair Rafique is the Lead Data Scientist at Marketlytics, a leading Digital Analytics consultancy in Karachi. He has been leading Data Science projects at Marketlytics for over 3 years, during which he has worked for multiple clients from Fortune 100.
His expertise lies in Statistical Analysis, Modelling, Machine Learning and Recommender Systems. Apart from that, he has been training aspiring Data Scientists in Statistical Inference and Regression Modelling with KarachiAI for the last 3 years.
Muhammad Hamza
Hamza is presently working as a Lead Data Scientist at Motive. With over 5 years of experience in the Data Science Industry, with past roles of Data Scientist at Daraz and Machine Learning Engineer at Gaditek. He has designed and deployed different data driven solutions including recommendations and predictive churn models in past.
He has teaching experience of over 2 years where he has taught courses related to Data Analytics, Data Engineering and Data Science.
Weekly Class Schedule
Here’s the tentative schedule for your course in the program. It’s designed to give you a clear understanding of what to expect. Please note that changes might occur, so consider this a general guide and stay updated for any revisions.
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Frequently Asked Questions
We provide three payment methods to eligible applicants:
Standard: A total fee of PKR 30,000, with an initial non-refundable registration fee of PKR 3,000. The remaining PKR 27,000 is payable in installments over 4-5 months.
Scholarship: A non-refundable registration fee of PKR 1,000 is required to apply. IEC offers a 50% scholarship on the course fee, you’ll pay PKR 15,000 during the course and the remaining PKR 50,000 in easy monthly installments after securing a job post-graduation.
Zakat: A non-refundable registration fee of PKR 500, with eligibility determined based on Islamic criteria.
Our programs are open to university students, recent graduates, and anyone passionate about learning and growing in the tech field.
The enrollment process at IEC is straightforward:
- Complete the application form
- Take an assessment test
- Undergo document verification
- Pay the registration fee
- Finalize enrollment
Professional development includes improving soft skills, creating a standout resume, optimizing your LinkedIn profile, and receiving mentorship to better prepare for the job market. IEC offers comprehensive support in all these areas through the best online courses in Pakistan.
Alumni Success
Muhammad Tayyab
Cohort 2
Hired as a Data Science Intern at
Faran Ahmad
Cohort 2
Hired as a Salesforce Data Quality Analyst at
