Data Science + AI Training
Combine the rigor of data science with the power of modern AI. This integrated program covers statistics, data wrangling, visualization, ML, deep learning and deployment. You will work with real industry datasets and build a portfolio of three end-to-end projects ready to share with recruiters.
Combine the rigor of data science with the power of modern AI. This integrated program covers statistics, data wrangling, visualization, ML, deep learning and deployment. You will work with real industry datasets and build a portfolio of three end-to-end projects ready to share with recruiters.
Syllabus
- Statistics for Data Science
- Data Wrangling with Pandas
- Visualization (Matplotlib, Seaborn, Plotly)
- SQL for Analysts
- ML & Model Selection
- Deep Learning Essentials
- Big Data Intro (Spark)
- Deployment & Storytelling
What you will learn
- Run end-to-end DS projects
- Build ML and DL models
- Tell stories with data
- Deploy a DS dashboard live
Tools you will use
- Python
- Pandas
- SQL
- Matplotlib
- Scikit-learn
- TensorFlow
- Tableau
- Streamlit
Projects
- EDA & dashboard for retail
- Predictive maintenance model
- NLP analytics on social data
- Capstone deployed dashboard
Career paths
- Data Scientist
- AI Analyst
- Business Intelligence Analyst
- Data Science Engineer
Who should join
- Graduates entering data
- Business analysts going technical
- Career changers
Prerequisites
- Basic Python helpful (we cover from scratch)
- High-school math
- Curiosity for problem-solving
Certificate
AI specialization certificate with deployed real-world AI projects in your portfolio.
Syllabus
- Statistics for Data Science
- Data Wrangling with Pandas
- Visualization (Matplotlib, Seaborn, Plotly)
- SQL for Analysts
- ML & Model Selection
- Deep Learning Essentials
- Big Data Intro (Spark)
- Deployment & Storytelling
Learning outcomes
- Run end-to-end DS projects
- Build ML and DL models
- Tell stories with data
- Deploy a DS dashboard live
Tools
- Python
- Pandas
- SQL
- Matplotlib
- Scikit-learn
- TensorFlow
- Tableau
- Streamlit
Projects
- EDA & dashboard for retail
- Predictive maintenance model
- NLP analytics on social data
- Capstone deployed dashboard
Career paths
- Data Scientist
- AI Analyst
- Business Intelligence Analyst
- Data Science Engineer
Who should join
- Graduates entering data
- Business analysts going technical
- Career changers
Prerequisites
- Basic Python helpful (we cover from scratch)
- High-school math
- Curiosity for problem-solving
Frequently asked questions
How is this different from pure AI?
Data Science emphasises analysis, business storytelling and decision-support alongside ML — perfect for analytics roles.
How long is the Data Science + AI Training course and how is it delivered?
The programme runs for 3-6 months and is available online & offline, with weekend and evening batches for working professionals.
What roles can I apply for after finishing?
Common target roles are: Data Scientist; AI Analyst; Business Intelligence Analyst; Data Science Engineer. Placement support covers resume building, mock interviews and referrals.