This program is built for absolute beginners who want to develop practical data science skills and prepare for entry-level careers in data analytics. Whether you’re a student, working professional, or career changer, you’ll learn how to collect, clean, analyze, visualize, and model real-world data using Python and industry-standard tools.
Across 8 weeks and 40 live sessions, you’ll progress from Python fundamentals to data analysis, SQL, statistics, machine learning, and portfolio development. Every week includes graded assessments, while the course culminates in two individual portfolio projects that you publish on GitHub. You’ll work with real datasets rather than simplified classroom examples, gaining experience with the same workflow used by professional data analysts.
By the end of the course, you’ll have more than theoretical knowledge. You’ll have a public GitHub portfolio, documented data science projects, and practical experience that demonstrates your ability to solve real business problems using data.
Why Choose This Training
- Learn by building, not watching. Around 60% of every class is spent writing code and solving practical problems.
- Learn the complete data workflow. From collecting raw data to building machine learning models and presenting insights.
- Build a portfolio, not just a certificate. Complete two individual GitHub projects using real-world datasets.
- Weekly feedback that improves your skills. Eight graded assessments with detailed instructor feedback throughout the program.
- Learn the tools employers expect. Python, pandas, SQL, Git, scikit-learn, Plotly, Streamlit, and more.
What You’ll Be Able to Do After This Course
- Write clean, structured Python code using functions, classes, and error handling
- Collect data from CSV, Excel, JSON, REST APIs, websites, and SQL databases
- Clean and prepare messy datasets for analysis
- Analyze data using NumPy and pandas
- Query databases using SQL, including joins and window functions
- Create professional charts and dashboards that communicate insights clearly
- Apply statistical techniques to support data-driven decisions
- Build and evaluate machine learning models using scikit-learn
- Publish documented data science projects on GitHub
- Present your findings with confidence using reports and visualizations
Tools & Platforms You’ll Work With
- Python
- VS Code
- Jupyter Notebook
- Google Colab
- NumPy
- pandas
- SQL & SQLite
- BeautifulSoup
- Requests API
- Matplotlib
- Seaborn
- Plotly
- scikit-learn
- Git & GitHub
- Streamlit
- Kaggle
Who This Course Is For
- Beginners with no programming experience
- BSc CSIT, BCA, BIM, BBA, BE, Statistics, and Economics students
- Professionals working with spreadsheets who want to upgrade to data analytics
- Career changers looking to enter the data industry
- Anyone interested in learning Python for data analysis and machine learning
No prior coding experience is required. The course starts from the fundamentals and gradually builds toward real-world data science projects.
Career Opportunities
Graduates are prepared to apply for roles such as:
- Junior Data Analyst
- Data Analyst
- Business Intelligence (BI) Analyst
- MIS / Reporting Analyst
- Junior Data Scientist
- Research & Insights Analyst
- Data Quality Analyst
- Marketing Analytics Associate
- Python Automation Associate
These opportunities exist across banks, fintech companies, IT service firms, telecom providers, e-commerce businesses, logistics companies, NGOs, research organizations, healthcare technology companies, and product startups.
Portfolio Projects You’ll Complete
- Project 1: Acquire, clean, analyze, and visualize a real-world dataset with a documented report and GitHub repository.
- Capstone Project: Build a complete end-to-end data science project incorporating data collection, statistical analysis, machine learning, visualization, and presentation.
- A public GitHub portfolio showcasing your projects with professional documentation and README files.
Certification
Participants who successfully complete the course, submit all required assessments and projects, maintain the required attendance, and present their capstone project receive an AITC Education Course Completion Certificate. High-performing students achieving 80% or above are awarded a Certificate of Merit, recognizing outstanding performance throughout the program.
