Data Science Training
Become a job-ready data professional. Learn Python, statistics, data wrangling, visualization and machine learning through hands-on projects on real datasets — with a capstone project and placement assistance.
What you learn in this Data Science course
Data Science combines programming, statistics and machine learning to turn raw data into decisions. As every industry — finance, healthcare, retail, SAP and IT services alike — invests in analytics and AI, the ability to clean, analyse and model data has become one of the most transferable and in-demand skillsets in tech.
This course takes you from Python fundamentals to building real machine learning models. You will wrangle data with pandas and numpy, visualize insights with matplotlib, seaborn and Power BI, query data with SQL, and train and evaluate regression, classification and clustering models with scikit-learn. Every concept is reinforced with lab work on real datasets so you leave with a portfolio of demonstrable projects.
Why Data Science skills are in demand
Data-driven decision making and the growth of AI are driving sustained demand for data science and analytics talent.
Data-Driven Decisions
Businesses in every sector rely on analytics and predictive models to guide strategy, creating steady demand for data talent.
AI & ML Adoption
Machine learning is now embedded in products from recommendations to fraud detection, expanding roles for ML-skilled professionals.
Cross-Industry Demand
Finance, healthcare, retail, e-commerce and IT services all hire data analysts and scientists, giving broad career flexibility.
Roles and earning potential
Indicative role titles and market salary ranges in India. Actual packages depend on experience, location and employer.
| Role | Experience | Indicative Salary (India, per year)* |
|---|---|---|
| Data Analyst | 0–2 yrs | ₹4–7 LPA |
| Data Scientist | 2–5 yrs | ₹8–16 LPA |
| Machine Learning Engineer | 2–5 yrs | ₹10–20 LPA |
| Senior Data Scientist / Lead | 6+ yrs | ₹25 LPA+ |
*Ranges are general market indicators compiled from public job data, not a guarantee of placement or salary.
Detailed Data Science curriculum
Structured modules that build from programming fundamentals to full machine learning workflows.
Week 1 Python Programming Foundations
- Python syntax, data types and control flow
- Functions, modules and error handling
- Working with files and libraries
- Jupyter Notebook workflow
Week 2 Statistics & Probability
- Descriptive statistics and distributions
- Probability fundamentals and sampling
- Hypothesis testing and confidence intervals
- Correlation and basic inferential statistics
Week 3 Data Wrangling with Pandas & NumPy
- DataFrames, indexing and cleaning messy data
- Handling missing values and outliers
- Merging, grouping and reshaping data
- NumPy arrays and vectorized operations
Week 4 Data Visualization & SQL
- Matplotlib and Seaborn for exploratory analysis
- Building dashboards in Power BI/Tableau
- SQL fundamentals for analytics queries
- Storytelling with data
Week 5 Machine Learning with Scikit-learn
- Regression algorithms (linear, logistic)
- Classification models (decision trees, random forest, SVM)
- Clustering (k-means) and unsupervised learning
- Feature engineering and preprocessing pipelines
Week 6 Model Evaluation & Tuning
- Train/test split, cross-validation
- Evaluation metrics (accuracy, precision, recall, RMSE)
- Hyperparameter tuning basics
- Avoiding overfitting and bias
Week 7 Real Datasets & Capstone Project
- End-to-end project on a real-world dataset
- Data cleaning through model deployment basics
- Portfolio and GitHub presentation
- Interview preparation for data roles
Technologies and tools you will use
Projects you will build
- Exploratory data analysis: clean and analyse a real-world dataset, visualize trends and present findings.
- Predictive modelling: build regression and classification models to solve a business problem.
- Capstone: an end-to-end data science project from raw data to a working, evaluated model.
- Graduates and engineers from any stream wanting to enter data science
- Analysts and BI professionals upgrading to ML skills
- Working professionals seeking a career switch into data roles
- Prerequisites: none required; basic logical/analytical thinking helps as programming is taught from scratch
Certification & Portfolio Readiness
Curriculum covers the core skills tested in leading data science and analytics certifications, plus you graduate with a portfolio of real projects and a GitHub profile to showcase to employers.
Placement Assistance
Resume building, data science interview questions, mock interviews, LinkedIn optimisation and referrals to hiring partners as part of our placement support.
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Start your Data Science journey
Contact our admissions team for the syllabus, next batch dates and a free counselling session.
Data Science Training — Frequently Asked Questions
What is Data Science?
Data Science is the practice of extracting insights and building predictive models from data using programming, statistics and machine learning — combining Python, data wrangling, visualization and ML algorithms to solve real business problems.
Who should take the Data Science course?
Graduates, engineers, analysts and working professionals from any background who want to build a career in data analytics, machine learning or AI. No prior coding experience is required.
Do I need a programming background to learn Data Science?
No. The course starts with Python programming fundamentals before moving into statistics, data analysis and machine learning, so complete beginners can follow along.
How long is the Data Science training?
The core program typically runs 8 to 10 weeks with instructor-led sessions, hands-on labs and a capstone project. Exact duration depends on the batch mode and pace.
Is the Data Science training available online and classroom?
Yes. Placeonix offers both instructor-led classroom training in Hyderabad and live online sessions, so you can choose the format that fits your schedule.
Will I work with real datasets?
Yes. Labs and projects use real-world public datasets so you practice data cleaning, exploratory analysis and model building on realistic, messy data rather than only toy examples.
What topics are covered in the Data Science curriculum?
Python programming, statistics and probability fundamentals, pandas/numpy for data wrangling, data visualization with matplotlib/seaborn/Power BI, SQL for analytics, machine learning (regression, classification, clustering) with scikit-learn, and model evaluation.
Which tools and technologies will I use?
Python, Jupyter Notebook, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, SQL, and Power BI or Tableau for dashboards and visualization.
Are there hands-on projects?
Yes. You build exploratory data analysis projects, regression and classification models, and a final capstone project on a real-world dataset, so you finish with a portfolio-ready GitHub project.
Does this course prepare me for data science certifications?
The curriculum covers the core skills assessed in widely recognised data science and analytics certifications. Trainers provide guidance on relevant certification paths and portfolio building for job readiness.
What job roles can I target after Data Science training?
Data Analyst, Data Scientist, Machine Learning Engineer, Business Intelligence Analyst and Data Science Trainee/Associate roles.
Is Data Science in demand?
Yes. Organisations across every industry are investing in data-driven decision-making and AI, making data science and analytics one of the fastest-growing tech career paths.
Do you provide placement assistance for Data Science?
Yes. Placeonix provides placement assistance including resume building, mock interviews, interview questions, LinkedIn optimisation and referrals to hiring partners.
What is the batch size?
Batches are kept small (maximum 30) so every learner gets individual attention and direct trainer feedback.
Can working professionals join?
Yes. Weekend and evening batches are available so working professionals can upskill without a career break.
Will I get a course completion certificate?
Yes. You receive a Placeonix course completion certificate along with a portfolio of projects to showcase to employers.
How is Data Science different from Generative AI?
Data Science covers the broader toolkit of statistics, analysis and traditional machine learning, while Generative AI focuses specifically on large language models, prompting and building AI-powered applications. Many learners study Data Science first and specialise into GenAI.
What is the fee for the Data Science course?
Fees vary by batch, mode and any combo package. Contact the Placeonix admissions team for the current Data Science course fee and available offers.
Do you offer combo packages with Generative AI?
Yes. A Data Science + Generative AI combo is available for learners who want end-to-end coverage from analytics to LLM applications, at a bundled price. Ask admissions for details.
Where is the Data Science training centre located?
Placeonix is located at Kapil Kavuri Hub, No. 144, 9th Floor, 152, Financial District, Hyderabad, Telangana 500032. Online training is available across India.
How do I enrol in the Data Science course?
Submit an enquiry on this page or call +91 99494 94020 / +91 91217 59191. The team will share the syllabus, next batch dates and a free counselling session.