Data Science Course in Chhatrapati Sambhajinagar (Aurangabad)

Data Science Course in Chhatrapati Sambhajinagar (Aurangabad)Classroom batchPlacement SupportInternship Support

Data Science Course in Chhatrapati Sambhajinagar (Aurangabad)

Name: Skillonit
Address: 3rd Floor, Shrishantul Tower, Chikhali Rd, Buldana, Maharashtra, 443002, IN
Telephone: +91 7083384100

Build practical skills in Python, SQL, statistics, data analysis, visualization, machine learning and AI with Skillonit's structured Data Science Course for learners in Chhatrapati Sambhajinagar (Aurangabad). The program is designed for beginners, students, graduates, freshers, working professionals and career switchers who want to learn through live explanation, guided practice and real-world projects. Learners in this city can join live online training, and classroom or hybrid options are shown only when verified Skillonit centre batches are active.

Start from the fundamentals, work with real datasets, build dashboards and machine learning models, complete portfolio-ready projects and receive career-preparation support throughout the learning journey. Learners in Chhatrapati Sambhajinagar (Aurangabad) can request current batch, fee and delivery-mode details from the admissions team.

Duration48 weeks

LanguagesHindi | English | Marathi

Rating4.7/5

Learners1,960

In-campus classroom training

Learners who want face-to-face teaching, fixed batches, and local classroom guidance.

Included in this mode

Instructor-led classroom sessionsIn-person doubt solvingComputer lab practiceBatch-wise assignments and tests

Learning flow

1Classroom orientation

2Guided practical sessions

3Weekly mentor review

4Project and certificate assessment

Data Science Training Available to Learners in Chhatrapati Sambhajinagar (Aurangabad)

Data skills are useful across technology, finance, retail, manufacturing, healthcare, education, logistics, marketing and professional services. Learners in Chhatrapati Sambhajinagar (Aurangabad) can use this course to build a foundation for analytical careers, strengthen their current role or prepare for advanced study in Machine Learning and Artificial Intelligence. Skillonit's curriculum connects technical skills to a complete workflow: understand a problem, access and clean data, write Python and SQL, explore patterns, create visual reports, build introductory machine learning models and explain results clearly.

Analyze real datasetsUse Python for modelingCreate dashboardsLearn statistical thinking

Why Learners in Chhatrapati Sambhajinagar (Aurangabad) Choose This Program

The course starts with the required foundations and does not assume that every learner is already a programmer or statistician. Sessions combine explanation, demonstration and hands-on work. The curriculum covers Python, SQL, data cleaning, statistics, exploratory analysis, visualization, business intelligence and introductory Machine Learning. Learners work on realistic problems and receive guidance on documentation, evaluation, presentation and improvement. Eligible learners receive resume, profile, portfolio and interview-preparation support. Skillonit provides assistance, not guaranteed employment.

Course level: beginner to intermediate with selected advanced concepts introduced practically

Recommended duration: approximately 3 months, generally 12-16 weeks depending on batch format

Live online training available across India

Classroom or hybrid delivery available only at verified Skillonit centres and announced batches

Complete Data Science Course Syllabus

Active module

Foundation

5 lessons

1Data Science, Analytics and the Modern Data Workflow: Data Science, Data Analytics, Machine Learning, Artificial Intelligence, Business Intelligence, analytical questions, data types, project lifecycles, data quality, ethics and communication.

2Computer, File, Spreadsheet and Development Environment Basics: files, folders, file extensions, cloud storage, command-line basics, spreadsheet essentials, Python setup, Jupyter Notebook, package installation and notebook organization.

3Python Programming Foundations: variables, values, data types, type conversion, operators, input and output, comments, conditional statements, loops, functions, parameters, return values, scope and error reading.

4Python Data Structures and Practical Problem Solving: strings, lists, tuples, dictionaries, sets, indexing, slicing, iteration, searching, sorting, aggregation, nested structures, comprehensions and basic file handling with text, CSV and JSON.

5NumPy for Numerical Computing: arrays, shapes, dimensions, selection, reshaping, vectorized operations, indexing, slicing, broadcasting, aggregation, statistical functions, random data and missing numerical values.

Upcoming Batch Schedule

Selected batch

Weekday Batch

Start DateUpcoming

TimingsRegular live sessions

Duration12-16 weeks

ModeOnline

Learn with Data Science Mentors

Skillonit's teaching approach combines clear explanation, guided practice, project review and career preparation. Trainers help learners understand not only how to run code but also how to define a problem, check data quality, choose an appropriate method and communicate findings responsibly. Verified trainer profiles should include professional photograph with consent, current role, relevant experience, core skills, selected project or industry exposure and a verified professional profile where available.

Kabir Sharma focuses on practical Data Science training with a learner-first approach. Sessions combine clear concept explanation, demonstrations, lab-based practice, and interview-oriented guidance so students understand how the skill is applied in real work.

Concept clarityProject practicePortfolio mentoring

Beginner-friendly explanations without oversimplifying important concepts

Live coding and step-by-step demonstrations

Practical examples connected to real analytical problems

Feedback on assignments, notebooks and projects

Guidance on debugging and improving code quality

Discussion of assumptions, limitations, bias and ethical use

Support in presenting projects and preparing for interviews

Data Science Certification from Skillonit

Eligible learners receive a Skillonit Data Science course-completion certificate after meeting the completion criteria defined for the batch. The certificate confirms participation and successful completion of Skillonit's internal learning requirements. It should not be described as a university degree, government licence or third-party professional certification unless a separate verified accreditation applies.

Minimum attendance as defined in the admission policy

Completion of required assignments or assessments

Submission of the capstone or final project

Participation in the final presentation or review

Adherence to academic integrity and project guidelines

Credential can complement a resume, LinkedIn profile and project portfolio

Certificate ID

SKL-DAT-2026

Certificate of Completion

Data Science Specialist

This certifies that the student has completed Skillonit’s Data Science training with practical tasks, quizzes, and project assessment.

Presented to

Student Name

For successful completion of Data Science Course

Completion Date

18 Jun 2026

★

Authorized Signature

Verification-ready certificate preview for LMS completion.

Course Highlights for Chhatrapati Sambhajinagar (Aurangabad) Learners

Course level: beginner to intermediate with selected advanced concepts introduced practically

Recommended duration: approximately 3 months, generally 12-16 weeks depending on batch format

Live online training available across India

Classroom or hybrid delivery available only at verified Skillonit centres and announced batches

Prerequisites: basic computer usage and willingness to practice

Prior programming experience is not compulsory

Main technologies: Python, Jupyter Notebook, NumPy, Pandas, Matplotlib, Seaborn, SQL, Excel, Power BI or Tableau, scikit-learn, Git and GitHub

Introductory exposure to TensorFlow, Keras, big data and model deployment

Learning format: live explanations, demonstrations, guided coding, practice exercises, assignments, case studies, mini projects, capstone work, doubt-clearing and project review

Tools students practice

Data ScienceDataPython for dataStatistics and probabilityMachine learningCapstone data project

Begin Your Data Science Learning Journey in Chhatrapati Sambhajinagar (Aurangabad)

This course blends clear concepts, practical training, guided projects, quizzes, and career-focused assessment to help learners build confidence and move toward real opportunities.

Learn core foundations

Practice with guided tasks

Complete project assessment

Prepare for career roles

Learn Data Science in Chhatrapati Sambhajinagar (Aurangabad) with a Practical Roadmap

Learners in Chhatrapati Sambhajinagar (Aurangabad) move through foundations, Python programming, data handling, SQL, statistics, exploratory analysis, visualization, dashboards, machine learning, portfolio building and career preparation. This local page is designed for learners who want clear access to the Data Science course from Chhatrapati Sambhajinagar (Aurangabad) while still following nationally relevant skills and project standards.

Role-focused learning

Live project practice

Portfolio-ready skills

Career and Placement Assistance

Skillonit provides career preparation and placement assistance to help eligible learners present their skills and approach suitable opportunities. Assistance is designed to improve readiness; it is not a promise of employment, a specific salary or a fixed interview timeline. Hiring decisions are made by employers and depend on skill, experience, education, portfolio, interview performance, location, role availability and other factors.

Placement Support Includes

Resume and project-description support for presenting skills, tools, projects and measurable contributions clearly

LinkedIn and professional-profile guidance including profile review, headline and summary guidance, project linking and consistent professional presence

GitHub and portfolio review for organization, documentation, reproducibility, confidentiality and readability

Mock interviews covering Python, SQL, statistics, machine learning basics, case questions, project discussion and behavioural communication

Job-search guidance on role selection, application quality, opportunity research, networking and interview follow-up

Freelancing and project guidance for defining analytical services, clarifying requirements, protecting client data, documenting scope and communicating results

Why Students Trust Us

Structured learning from foundations to projects

Practical, guided learning through demonstrations, coding, exercises and project work

Beginner-friendly explanations with examples and incremental practice

Project and portfolio development that prioritizes quality over unfinished project count

Flexible live online access across India with classroom options only where verified

Responsible use of data and AI with discussion of privacy, bias, fairness, limitations and ethical communication

Continued learning roadmap for analytics, BI, Machine Learning, AI, Data Engineering or advanced project work

Admission enquiry

Talk to a Skillonit counsellor

Share your details and our team will help you choose the right Data Science batch, learning mode, syllabus, fee plan, and career path.

Request Callback+91 7083384100

Download SyllabusData Science course outline

WhatsApp GuidanceFast response from counsellor

Who Can Join the Data Science Course in Chhatrapati Sambhajinagar (Aurangabad)?

College students can build practical skills alongside their degree. Fresh graduates can prepare for entry-level analytics, reporting, BI and Data Science opportunities that match their overall profile. Working professionals can strengthen data-driven decision-making or prepare for a transition into analytics, BI, Machine Learning or related roles. Non-IT learners from commerce, management, science, arts and other backgrounds can join, though additional programming practice may be required. Entrepreneurs and freelancers can learn customer data analysis, performance reporting, forecasting, dashboard development and introductory analytical projects.

Career roles

Data Trainee

Build strong foundation skills in Data Science

Project Intern

Apply concepts through guided practical projects

Freelance Beginner

Use portfolio work to start client-ready practice

Career Starter

Prepare for internships, jobs, or higher learning

Why Choose Skillonit for Data Science Training in Chhatrapati Sambhajinagar (Aurangabad)?

Structured beginner-to-project learning pathway

Practical classes with exercises and assignments

Python, SQL, statistics, visualization and Machine Learning in one program

Guided project and portfolio development

Live online access across Chhatrapati Sambhajinagar (Aurangabad)

Classroom information only where a real centre and active batch exist

Career-preparation support with transparent expectations

Responsible discussion of data quality, privacy, bias and limitations

Clear next-step guidance for Data Analytics, BI, Machine Learning, AI or Data Engineering

Internship Program

Data Science Internship Program in Chhatrapati Sambhajinagar (Aurangabad)

Skillonit’s Data Science Internship Program in Chhatrapati Sambhajinagar (Aurangabad) is a mentor-guided practical pathway available in 1-month, 3-month and 6-month formats. Participants learn how to solve data problems through Python, SQL, statistics, data cleaning, exploratory analysis, visualization, machine learning, experimentation and model communication. The program combines structured training, assignments, project reviews, documentation, portfolio support and a completion certificate subject to published requirements.

The internship is designed for students, graduates, analysts, developers, researchers, working professionals and career switchers. It turns course knowledge into structured practice through mentor-led onboarding, guided tasks, project milestones, review meetings, documentation and a final presentation. Participants are expected to build, test, explain and improve their work instead of only watching demonstrations.

1 month3 months6 monthsChhatrapati Sambhajinagar (Aurangabad), India

Apply Now

Available durations

1 month, 3 months and 6 months

Delivery modes

Live online, classroom or hybrid—subject to the selected batch and location

Local availability

Local centre, mode, start date and seat availability are shared only from verified city data.

Learning model

Training + mentor-guided tasks + project reviews + portfolio evidence

Projects

Mini project, guided projects and capstone according to duration

Support

Onboarding, doubt clearing, task planning, review feedback and presentation guidance

About Program

About the Internship Program

Skillonit’s Data Science internship is designed as a bridge between learning and practical delivery. Interns begin with a baseline assessment and a clear task plan, then progress through demonstrations, guided exercises, independent work and review. The focus is on understanding why a solution works, how to communicate decisions and how to improve quality after feedback.

The work is aligned with Python, SQL and spreadsheet-based data work, feature engineering and predictive modelling and advanced machine learning and time-series work. Longer pathways include more complex requirements, collaboration, documentation, testing and presentation. Interns maintain a task log or project board so that progress can be reviewed objectively rather than judged only by the final output.

The internship does not guarantee employment, freelance income, client allocation or a stipend. It provides practical exposure, evidence of completed work and career-readiness support. Any employment or paid internship opportunity is published separately with its own eligibility, application deadline, compensation and selection process.

Duration Options

Choose your internship duration

Option 1

1-Month Data Science Foundation Internship

The one-month pathway is a focused four-week experience for learners who want an introduction to professional data science practice. It prioritizes orientation, essential tools, one clear workflow and a mentor-reviewed mini project. It is most suitable for beginners, students testing the domain, or course learners who need a short practical component.

Week 1 – Orientation and foundation: skill assessment, program rules, tool setup, task tracking, Python, SQL and spreadsheet-based data work and a short guided exercise.

Week 2 – Core practice: data cleaning and exploratory analysis, mentor demonstration, individual practice and a quality checklist.

Week 3 – Mini project build: apply statistics, visualization and business problem framing to a scoped project with milestone review and corrections.

Week 4 – Finalization: testing or quality review, documentation, presentation, mentor feedback and next-learning roadmap.

Expected 1-month evidence: One completed mini project, task log, project summary, mentor feedback record and final presentation. Example project: Sales and customer analysis.

Option 2

3-Month Data Science Applied Internship

The three-month pathway is the recommended option for learners who want meaningful portfolio evidence. It combines a foundation phase, an applied phase and a capstone phase. Interns work on at least two guided assignments and one larger project, with regular reviews that focus on quality, documentation and problem-solving.

Month 1 – Foundation and workflow: Python, SQL and spreadsheet-based data work, data cleaning and exploratory analysis, statistics, visualization and business problem framing; tool setup; guided exercises; communication and documentation standards.

Month 2 – Applied delivery: feature engineering and predictive modelling, model evaluation and experiment design, dashboards, storytelling and stakeholder communication; first project review; debugging, critique or analysis; iteration after feedback.

Month 3 – Capstone and portfolio: build Demand or sales forecasting or another approved project; complete testing, documentation, presentation and portfolio packaging.

Expected 3-month evidence: Two guided projects, one capstone, weekly progress records, review notes, final presentation and a portfolio-ready case study. Suggested project options include Customer churn prediction, Demand or sales forecasting and Recommendation system.

Option 3

6-Month Data Science Advanced Internship

The six-month pathway is intended for learners seeking deeper, sustained practical experience. It includes specialization, team workflow, quality assurance and a production-style capstone. Interns gradually take greater ownership while remaining accountable to scope, security, ethics and mentor review.

Month 1 – Foundation: Python, SQL and spreadsheet-based data work and data cleaning and exploratory analysis, baseline tasks and work standards.

Month 2 – Core build: statistics, visualization and business problem framing plus the first guided project and review cycle.

Month 3 – Applied specialization: feature engineering and predictive modelling and model evaluation and experiment design with an intermediate project.

Month 4 – Integration: dashboards, storytelling and stakeholder communication and cross-functional workflow, documentation and quality checks.

Expected 6-month evidence: A structured portfolio containing three or more projects, an advanced capstone, documented iterations, mentor reviews, a presentation and a skills matrix. Suggested advanced projects include Recommendation system, Fraud or anomaly detection study and End-to-end data science capstone.

Skills and Tools

What Interns Will Learn and Practice

Foundation skills: Python, SQL and spreadsheet-based data work, data cleaning and exploratory analysis, statistics, visualization and business problem framing.

Applied skills: feature engineering and predictive modelling, model evaluation and experiment design, dashboards, storytelling and stakeholder communication.

Advanced skills: advanced machine learning and time-series work, model deployment and MLOps awareness, end-to-end data product delivery.

Problem decomposition, requirement clarification and task estimation.

Professional communication, asking useful questions and reporting blockers early.

Documentation, version control or evidence management appropriate to the domain.

Quality assurance through testing, review, critique, validation or rehearsal.

Portfolio presentation that explains the problem, process, decisions, result and lessons learned.

Working Environment

Tools, Platforms and Working Environment

The exact stack may vary by batch and project. Typical tools include Python, Jupyter, pandas, NumPy, Matplotlib, Seaborn, SQL, Power BI or Tableau, scikit-learn, GitHub, Streamlit or FastAPI. Skillonit should publish only the tools that are actually supported in the selected batch and provide setup guidance, access requirements and alternatives where paid licences are involved.

Project Practice

Live Projects and Portfolio Work

Real client projects are included only when an approved project, permission and review process are available; otherwise learners work on realistic industry simulations or mentor-designed capstones.