Course Description
This course is designed to equip learners with essential skills in data analytics using Python and Tableau, with a strong emphasis on real-world applications. Participants will gain hands-on experience in data cleaning, exploratory analysis, and visualisation, enabling them to transform raw data into meaningful insights that support data-driven decisionmaking. The course combines technical foundations with practical project work, preparing learners for entry-level data analyst roles and applied analytics tasks across various domains.
Course Details
Regular Course Fee : BDT 10,000
Discounted Course Fee : BDT 7,000
( New Year Offer)
Class Type
Weekly Two Classes
Class Date & Time
Time: 9:30PM - 11:00PM
Total : 24 Hours Course
Mode of Training
Online
Trainer Profile
Name
Nasrin Akter
Expertise
Data Science, Machine Learning, AI & Deep Learning
Institution
Former lecturer of Daffodil Institute of Information Technology (DIIT)
Experience
15+ years of Industry Experience
Learning Outcome of Training
Clean and analyze datasets using Python
Perform exploratory data analysis effectively
Create meaningful visualizations using Python and Tableau
Build interactive dashboards for real-world scenarios
Present data-driven insights clearly and confidently
Course Contents Details
Lecture 1: Introduction to Data Analytics and Python
• Overview of Data Analytics and Real-World Applications
• The Data Analytics Lifecycle
• Introduction to Python for Data Analysis
• Setting Up the Python Environment
Lecture 2: Data Manipulation and Analysis with Python
• Introduction to Pandas for Data Handling
• Data Analysis with NumPy
• Working with Different Data Formats (CSV, Excel)
• Exploratory Data Analysis (EDA) Techniques
Lecture 3: Data Visualization with Python
• Principles of Effective Data Visualization
• Data Visualization Using Matplotlib
• Advanced Visualization Using Seaborn
Lecture 4: Data Cleaning and Preparation
• Data Quality Issues and Missing Values
• Data Cleaning and Transformation Techniques
• Importing and Exporting Data in Python
Lecture 5: Data Visualization and Dashboards with Tableau
• Introduction to Tableau and Its Interface
• Creating Interactive Visualizations
• Building Dashboards for Business Insights
• Connecting Python-Prepared Data with Tableau
Lecture 6: Project Planning and Dataset Understanding
• Defining a Real-World Data Analytics Problem
• Understanding Business Questions and Objectives
• Dataset Exploration and Feature Understanding
Lecture 7: Project Implementation – Python & Tableau
• End-to-End Data Analysis Project
• Applying Analytical and Visualisation Techniques
• Best Practices and Common Pitfalls in Data Analytics
Lecture 8: Project Presentation and Evaluation
• Project Demonstration
• Insight Presentation and Data Storytelling
• Peer Review, Feedback, and Discussion
Career Benefits:
Versatility Across Industries:
Data analysis skills are applicable across various sectors, including finance, healthcare, marketing, and technology, offering diverse career opportunities.
Enhanced Problem-Solving Abilities:
Learning data analysis cultivates critical thinking and problem-solving skills, making you a valuable asset to any team.
Competitive Salary:
Data analysts often enjoy competitive salaries due to the demand for skilled professionals in this field.
Ability to Influence Decisions:
Understanding data allows you to provide insights that can directly impact strategic decisions, enhancing your influence within an organization.
Portfolio Development:
Working on real-world projects using Python and Tableau helps you build a strong portfolio that showcases your skills to potential employers.
Remote Work Opportunities:
Many data analysis roles offer flexibility and the possibility of remote work, enhancing work-life balance.
Roles & Industry Demand
Common R0les
Business Intelligence (BI) Analyst
Data Analyst (Generalist)
Marketing Analyst
Financial Analyst
Operations Analyst & Product Analyst
Demand in Industry:
Healthcare & Life Sciences
Finance & Fintech
E-commerce & Retail
Energy & Sustainability
Assessment Strategy
Project implementation and final presentation
Demonstrated understanding of analytical concepts
Participation in hands-on activities and discussions
Why Choose Our Training?
Expert Trainer
Interactive Labs
Study Resources
Mentor Support
Frequently Asked Questions:
FAQ answered:
This course is a hybrid program designed to teach you the end-to-end data pipeline. You use Python for the heavy lifting—cleaning messy data, automating tasks, and performing complex statistics—and Tableau to transform those results into interactive, executive-ready dashboards.
Python is the "engine": It handles massive datasets and complex logic that Tableau might struggle with.
Tableau is the "steering wheel": It’s the best tool for letting non-technical stakeholders (like Managers or CEOs) "drive" the data themselves through filters and clicks.
Basic Math/Stats: Understanding averages, medians, and percentages.
Excel Literacy: Familiarity with rows, columns, and basic formulas (like SUM or IF).
No Prior Coding Needed: Most versions of this course (like the Google or UT Dallas versions) start Python from the absolute basics (variables, loops, and lists).
• A computer with Python and Tableau installed
• Datasets and supplementary learning resources (provided by the institute)
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