Requirements
- Basic computer skills (file handling, internet, installing software)
- Comfort with numbers (basic math: % , average, ratios; not advanced)
- Basic statistics understanding (mean/median, probability basics)
- Logical thinking (if-else type reasoning, problem-solving mindset)
- Excel basics (filters, sorting, simple formulas) — helpful
- Programming basics (optional): not mandatory, but helps if you know any language
- Laptop/PC: minimum 8GB RAM (16GB recommended), i5/Ryzen5 or similar
- Stable internet for online sessions and project downloads
- Willingness to practice: 5–8 hours/week for assignments + projects
Features
- Live Project-Based Training
- Expert-Led Sessions
- Flexible Learning Options
- Interactive Learning
- Smart Labs with Advanced Equipment
- Unlimited Lab Access
- Comprehensive Study Material
- Globally Recognized Certification
- One-on-One Mentorship
- Career Readiness
- Job Assistance
Target audiences
- 12th pass students (from any stream) who want an IT career start
- College students (BCA/BSc/BTech/BE/BA/Commerce) planning data roles
- Fresh graduates looking for Data Analyst / Jr Data Scientist jobs
- Working professionals who want a career switch into data/AI
- Software developers who want to move into ML/AI projects
- Business/Finance/Marketing professionals who want data-driven skills
- Excel/MIS/Reporting professionals upgrading to analytics + Python
- Professionals preparing for higher studies or research in AI/ML
- Entrepreneurs/startup teams who want to use data for decisions
Data Science Course in Ghaziabad | Data Science Training in Ghaziabad
By the end of the Data Science Course in Ghaziabad with placement support, learners typically leave with a portfolio of projects, stronger confidence in analytics and ML fundamentals, and interview readiness for entry-level roles in data and analytics.
Course Overview
The Data Science Course in Ghaziabad at Ascents Learning is designed around real work scenarios: messy data, practical decision-making, and model performance that must be explained to others.
You’ll learn to:
- Collect and prepare data (Excel/CSV, SQL databases, APIs basics)
- Perform EDA (exploratory data analysis) and identify trends
- Apply statistics for business decisions (sampling, hypothesis testing)
- Build ML models (regression, classification, clustering)
- Evaluate models with correct metrics (F1, ROC-AUC, RMSE, MAE)
- Communicate insights using dashboards and storytelling
- Create a portfolio that recruiters can review
Who Should Enroll
This Data Science training in Ghaziabad is a fit if you want a structured path, hands-on practice, and project output you can show.
Students (UG/PG)
- Want internship-ready skills and projects
- Need a clear learning roadmap beyond theory
Freshers
- Want a portfolio + interview preparation
- Need practical exposure to Python, SQL, and dashboards
Working Professionals
- Want to switch into data roles from IT, operations, sales, finance, support, or QA
- Prefer guided training with mentor feedback
Career Switchers
- Want a step-by-step transition plan into analytics/data science
- Need a practical, tool-based approach rather than only lectures
Good to have (not mandatory)
- Comfort with basic math and charts
- Willingness to practice regularly
Learning Outcomes
After completing the Data Science Course in Ghaziabad, you should be able to handle common data tasks end-to-end.
Data Handling & SQL
- Clean and preprocess datasets (missing values, outliers, inconsistent text)
- Use Pandas and NumPy for analysis
- Write SQL queries for analytics: SELECT, WHERE, GROUP BY, JOINS, aggregations, filtering, and window functions (basics)
Statistics & Decision-Making
- Understand distributions and variability
- Use confidence intervals in real situations
- Apply hypothesis testing with correct assumptions
- Avoid common errors (data leakage, wrong metric selection)
Machine Learning (Practical)
- Train models using scikit-learn
- Build regression, classification, and clustering models
- Evaluate with accuracy, precision, recall, F1, ROC-AUC, RMSE, and MAE
- Improve models using feature engineering and tuning
Visualization & Communication
- Create charts in Matplotlib / Plotly
- Build dashboards in Power BI or Tableau
- Explain outputs clearly to non-technical stakeholders
Portfolio & Collaboration
- Use Git/GitHub for version control
- Document projects (problem → approach → results → next steps)
- Prepare a resume and project walkthrough for interviews
Teaching Methodology
Ascents Learning runs the Data Science training in Ghaziabad with a practical structure so learners don’t get stuck at “watched videos but can’t apply.”
Typical learning format:
- Hands-on instructor-led sessions
- Guided labs in Python/SQL
- Weekly assignments for consistency
- Mini projects after major modules (EDA, SQL, ML, dashboards)
- Capstone project (end-to-end)
- Mentor reviews and doubt clearing
- Placement support: resume/LinkedIn optimization, portfolio guidance (GitHub), mock technical + HR interviews
This approach helps learners build output that can be shown in interviews, which matters for anyone targeting a
Data Science Course in Ghaziabad With Placement support.
Tools & Technologies Covered
This Data Science Course in Ghaziabad covers the tools commonly used in analytics and entry-level data science teams.
Programming & Notebooks
- Python
- Jupyter Notebook (and Colab basics)
Data Analysis
- Pandas
- NumPy
Visualization
- Matplotlib
- Plotly
Databases
- SQL (MySQL/PostgreSQL concepts)
Machine Learning
- scikit-learn
- Model evaluation, cross-validation basics
- Pipelines and feature engineering concepts
BI & Reporting
- Power BI or Tableau (dashboards, KPIs, filters, visuals)
Collaboration
- Git
- GitHub
- Basic project structuring and documentation
Intro Modules (optional/intro level)
- NLP basics (text cleaning, vectorization)
- Time series basics (trends, seasonality concepts)
- API basics and deployment concepts (Flask/FastAPI overview)
Certification & Industry Recognition
On completion, learners typically receive a certificate from Ascents Learning that reflects the track covered under the Data Science Course in Ghaziabad.
What makes the certification more useful in hiring:
- Projects that show practical problem solving
- A GitHub portfolio with readable notebooks and code
- Clear documentation and outcomes, not just screenshots
Recruiters usually focus on your project clarity and tool skills. The certificate helps, but the portfolio does the heavy lifting.
Career Opportunities After Completion
After the Data Science Course in Ghaziabad with placement support, many learners aim for entry-level roles based on their background and project quality.
Common roles:
- Data Analyst
- Junior Data Scientist
- Business Analyst (data-focused)
- BI Analyst (Power BI / Tableau)
- Machine Learning Intern / Trainee
- Product Analyst (analytics-heavy teams)
Skills employers commonly check:
- Python + SQL fundamentals
- EDA and data cleaning ability
- Correct metric usage and model evaluation
- Dashboard/reporting basics
- Ability to explain work clearly
- A portfolio of 2–4 relevant projects
Why Choose Ascents Learning
If you’re comparing the Best Data Science Course in Ghaziabad, focus on how much practical output you’ll build during the program.
Ascents Learning is chosen for:
- Practical, hands-on learning with real datasets
- Industry-style projects and a capstone
- Mentor guidance and structured doubt clearing
- Strong focus on tools used in hiring (Python, SQL, Power BI/Tableau, GitHub)
- Placement support: resume, portfolio, and mock interviews
- Flexible learning modes (online/offline/hybrid based on batch availability)
Ascents Learning aims to function as a reliable Data Science Training Institute in Ghaziabad by keeping the training centered on job tasks, not just theory.
If you want a practical Data Science Course in Ghaziabad with structured learning and placement support, connect with Ascents Learning to get batch details, curriculum flow, and guidance on the right learning track. Website: www.ascentslearning.com
Curriculum
- 6 Sections
- 146 Lessons
- 22 Weeks
- Module 1: Python FundamentalsIntroduction to Python26
- Module 2: SQL and Database FundamentalsIntroduction to Databases53
- Module 3: ML Statistics for BeginnersIntroduction: Role of statistics in ML, descriptive vs. inferential stats. Descriptive Statistics: Mean, median, variance, skewness, kurtosis. Probability Basics: Bayes' theorem, normal, binomial, Poisson distributions. Inferential Statistics: Sampling, hypothesis testing (Z-test, T-test, Chi-square). Correlation & Regression: Pearson correlation, linear regression, R² score. Hands-on in Python: NumPy, Pandas, SciPy, Seaborn, and statsmodels.57
- Module 5: ML Model Deployment with Flask, FastAPI, and Streamlit6
- Module 6: Final Capstone ProjectDevelop an end-to-end solution that integrates multiple technologies:1
- Tools & Technologies Covered3




