Python Training
Start with Python programming if you want to build a strong foundation before moving deeper into Data Science, automation, backend development, or AI.
View Python CourseLearn Data Science through offline classroom training at Zestminds Academy in Mohali. This 6-month program is designed for beginners, BCA, MCA, B.Tech, M.Tech students, and freshers who want to build practical skills in Python, data analysis, machine learning, visualization, and project-based problem solving.
Suitable for beginners, BCA, MCA, B.Tech, M.Tech students, freshers, and students looking for practical Data Science training.
Learn Data Science in a structured classroom environment with mentor guidance and regular practice.
Build skills in Python, Pandas, visualization, machine learning, data preparation, and model workflows.
Work with datasets, assignments, mini-projects, and capstone-style practical learning.
Get a course completion certificate along with resume, interview, and project presentation guidance.
This course is suitable for students who want to understand how data is cleaned, analyzed, visualized, modeled, and presented in real project workflows.
Start with Python and Data Science foundations before moving toward data analysis, machine learning, and projects.
Build practical technical skills that support college projects, internships, fresher preparation, and portfolio work.
Useful for learners confused between Data Analytics, Data Science, Machine Learning, and AI career paths.
Students learn the complete journey of working with data, from cleaning and analysis to visualization, machine learning, deployment basics, and final project presentation.
The aim is not only to teach commands. Students learn why each step matters inside a real data workflow.
The program is divided into practical learning stages so students can move from foundations to project-level implementation.
Learn Python logic, variables, data types, conditions, loops, functions, files, and practical coding habits.
Work with structured data, tables, rows, columns, missing values, grouping, filtering, and transformation.
Handle duplicate records, missing values, incorrect formats, outliers, and inconsistent data before analysis.
Study patterns, compare values, identify relationships, and ask better questions from a dataset.
Create charts and visual reports using Matplotlib and Seaborn to explain trends and insights clearly.
Understand averages, distributions, variance, correlation, probability basics, and their role in analysis.
Learn regression, classification, clustering, train-test split, model evaluation, overfitting, and underfitting basics.
Get introduced to feature engineering, hyperparameter tuning, model comparison, and performance improvement.
Understand neural network basics and get beginner-level exposure to TensorFlow and Keras concepts.
Learn ETL workflow basics, data pipelines, Hadoop, Spark, and PySpark concepts at an introductory level.
Understand Git, GitHub, project structure, and basic Flask/Django-based deployment ideas.
Apply data cleaning, visualization, machine learning, and presentation skills in one guided project workflow.
Students work with tools used in practical Data Science learning, analysis, model building, and project presentation.
| Category | Tools / Technologies |
|---|---|
| Programming | Python |
| Data Handling | NumPy, Pandas |
| Visualization | Matplotlib, Seaborn |
| Machine Learning | Scikit-learn |
| Deep Learning Basics | TensorFlow, Keras |
| Big Data Exposure | Hadoop, Spark, PySpark |
| Deployment Basics | Flask / Django concepts |
| Workflow | Git, GitHub |
| Project Practice | Jupyter Notebook and practical coding environment |
Tools are introduced through examples and practice so students understand where each tool fits inside a real data workflow.
Data Science cannot be learned properly by only reading theory. Students need to work with datasets, make mistakes, debug problems, and understand how data decisions are made.
Analyze sales datasets to identify trends, patterns, product performance, and useful business insights.
Practice clustering and segmentation concepts to understand customer groups and behavior patterns.
Work on messy datasets and prepare them for analysis by handling missing values, duplicates, and format issues.
Create visual summaries that explain patterns, comparisons, and important observations from data.
Build beginner-friendly machine learning models and learn how to evaluate their performance.
Apply data preparation, visualization, ML concepts, and project presentation in one complete workflow.
Project examples may vary by batch and student level. The aim is to help students understand practical Data Science work and explain their project approach with confidence.
Clear course details help students and parents understand the fee, duration, and learning format before enrolling.
| Detail | Information |
|---|---|
| Course Duration | 6 Months |
| Training Mode | Offline classroom training |
| Location | Mohali |
| Monthly Fee | ₹4,000 per month |
| 3-Month Fee Reference | ₹12,000 |
| 6-Month Program Fee | ₹24,000 |
| Batch 1 | 9 AM–12 PM |
| Batch 2 | 1 PM–4 PM |
| Suitable For | Beginners, BCA, MCA, B.Tech, M.Tech students, and freshers |
| Certificate | Certificate after course completion |
Students can contact the academy to check current seat availability, batch timing, syllabus details, and counselling options.
This course does not promise guaranteed jobs or fixed salary outcomes. The focus is on helping students become more skilled, confident, and better prepared for entry-level opportunities, internships, and interviews.
Get support in presenting your skills, course learning, tools, and project work clearly on your resume.
Practice explaining Data Science concepts, project logic, tools used, and challenges faced during project work.
Learn how to organize project work, prepare project summaries, and present your learning more professionally.
After completing the course sincerely, students should be able to understand core Data Science workflows, work on beginner-to-intermediate projects, explain their learning clearly, and continue building toward data-related roles.
Zestminds Academy is built for students who want practical software and data training, not only classroom theory.
Students learn by writing code, working with datasets, solving errors, and building practical project workflows.
The training approach is influenced by real software development practices, project workflows, and debugging habits.
Assignments, datasets, mini-projects, and capstone work help students connect concepts with practical application.
Classroom learning helps students ask doubts, stay consistent, and learn with a structured routine.
Students receive support with resume, interviews, project explanation, portfolio readiness, and learning direction.
Students learn in an academy connected with a real software development environment and practical project thinking.
Zestminds Academy offers offline Data Science training in Mohali for students who prefer classroom learning, mentor guidance, and practical project exposure.
Students from nearby locations can contact the academy to discuss course duration, fee, batch timing, and whether Data Science is the right path for their current background.
Address: E-45, Industrial Area, Phase 8, Mohali
Phone: 919056277961
Email: hello@zestmindsacademy.com
Common questions students and parents ask before joining Data Science training at Zestminds Academy.
If you are still exploring the right learning path, these related courses can help you choose between programming, data analytics, full stack development, AI, and internship-based training.
Start with Python programming if you want to build a strong foundation before moving deeper into Data Science, automation, backend development, or AI.
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View Analytics CourseExplore AI and Machine Learning if you want to move deeper into models, intelligent systems, LLM concepts, and advanced AI workflows.
View AI CourseChoose internship training if you want longer practical exposure, project-based learning, mentor guidance, and career-focused preparation.
View Internship ProgramConfused between Data Science, Data Analytics, Python, AI, or Internship Training? Talk to our team before choosing your course.
Book Free Course Counselling Ask on WhatsAppTalk to our team, understand the syllabus, check current batch details, and discuss whether Data Science fits your background. We can help you compare Data Science, Data Analytics, Python, AI, and Machine Learning before you choose.
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