Technology Training · Data & Analytics
Data Science Training
Combine statistics, Python and machine learning to solve real problems — from data wrangling to predictive models.
- Python
- Jupyter Notebook
- Pandas
- NumPy
Course overview
Data Science Training Overview
Data Science training brings together programming, statistics and machine learning to extract insight and build predictive models.
You learn to collect and wrangle data, explore it visually, test hypotheses, build and evaluate machine learning models, and communicate results to technical and non-technical audiences.
Course syllabus
What You'll Learn in Data Science Training
- The data science lifecycle
- Python, NumPy and Pandas for data wrangling
- Exploratory data analysis and visualisation
- Probability and inferential statistics
- Hypothesis testing and A/B testing
- Regression and classification models
- Clustering and segmentation
- Feature engineering and model selection
- Model evaluation and interpretation
- Presenting data science results
Tools & technologies
Tools & Technologies Covered
- Python
- Jupyter Notebook
- Pandas
- NumPy
- scikit-learn
- Matplotlib
- Seaborn
- SQL
Who should join?
Who Should Join Data Science Training?
Graduates in science, engineering & commerce
Apply your quantitative background to data problems.
Data analysts
Progress from analysis to predictive modelling.
Developers
Add statistics and machine learning to your skill set.
Researchers
Use modern data tools for research projects.
Prerequisites: Basic programming knowledge and school-level mathematics are recommended.
Career paths
Career Opportunities After Data Science Training
Common roles for professionals with Data Science skills:
- 01Data Scientist
- 02Machine Learning Engineer
- 03Data Analyst
- 04Decision Scientist
- 05Analytics Consultant
Career outcomes depend on your background, practice and the job market. We focus on practical skills and do not promise guaranteed placement.
FAQ
Data Science: Frequently Asked Questions
What will I learn in the Data Science course?
The Data Science training covers the data science lifecycle, python, NumPy and Pandas for data wrangling, exploratory data analysis and visualisation, probability and inferential statistics, hypothesis testing and A/B testing, regression and classification models, clustering and segmentation, feature engineering and model selection, model evaluation and interpretation and presenting data science results.
Which tools are covered in Data Science training?
You will work with Python, Jupyter Notebook, Pandas, NumPy, scikit-learn, Matplotlib, Seaborn and SQL.
Who can join the Data Science course?
The course suits graduates in science, engineering & commerce, data analysts, developers and researchers. Basic programming knowledge and school-level mathematics are recommended.
What jobs can I apply for after learning Data Science?
Common roles include Data Scientist, Machine Learning Engineer, Data Analyst, Decision Scientist and Analytics Consultant. Career outcomes depend on your background, practice and the job market.
How do I get the Data Science syllabus, duration, fees and batch details?
Contact us on WhatsApp or through the enquiry form and our team will share the current Data Science syllabus, course duration, fees and upcoming batch details.
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Ready to Start Data Science Training?
Talk to our team about the Data Science syllabus, course duration, fees and upcoming batch details.
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