01
Understand
Study the business question and understand the available dataset.
Problem • Data
Practical IT Training in Indore
Data Science & AI Course in Indore for practical skills, projects and certification.
Work with data analysis, visualisation, machine learning models and practical artificial intelligence applications. Learn through structured sessions, guided practice, assignments and industry-style projects with CISS IT Training.
Learn through mentor-led sessions, guided implementation, hands-on assignments and real-world projects while building practical confidence and working toward course completion certification.
Mentor-led practical trainingReal project experienceCourse certificationIndore, Madhya Pradesh
Duration
6 months
Training mode
Online / Hybrid
Level
Intermediate
Project work
6 practical projects
Completion
Certification
Location
Indore, MP
Core stack
PythonPandasMachine LearningAIData to decision workflow
Understand how raw information becomes analysis, models and useful decisions.
Practical data work starts with imperfect information. Learners clean data, explore patterns, build analysis and evaluate models before communicating useful results.
Example product
Business Analytics & Prediction System
Real-world scenario
Historical business information is cleaned and analysed to identify patterns, build predictions and support decisions.
Typical users
Analysts, managers and decision makers
02
Implement
Clean, transform, analyse and visualise the information.
Python • Analytics
03
Verify
Evaluate the analysis or model and check the quality of results.
Metrics • Testing
04
Present
Communicate findings, decisions and project outcomes clearly.
Insights • Storytelling
How the course is structured
Learn with a clear practical purpose at every stage.
The course is designed around understanding, implementation and practical demonstration rather than memorising isolated syntax.
Understand
Build strong fundamentals before adding complexity.
Data Science and Applied AI helps learners transform raw data into meaningful analysis and build practical machine learning and artificial intelligence solutions.
Implement
Use real technologies inside practical workflows.
Work with Python, Pandas, Machine Learning, AI and understand where each technology fits in the development process.
Demonstrate
Turn learning into work you can explain confidently.
Build practical project work, solve implementation problems and learn to explain your approach during project reviews and interviews.
Who should join?
Students interested in data and artificial intelligence
Python learners progressing into data-focused roles
Professionals working with data-driven workflows
Developers exploring practical AI applications
Before you begin
Basic Python knowledge is helpful
Comfort with basic mathematics
Interest in working with data and logical problems
Learning outcomes
Focus on what you can actually do after the course.
The objective is practical capability — understanding concepts, implementing features, solving problems and explaining your work.
01
Understand the core concepts used in Data Science and Applied AI
02
Use Python, Pandas, Machine Learning in practical exercises
03
Build structured projects instead of learning through theory alone
04
Debug common implementation problems using a systematic workflow
05
Use Git and professional development practices where applicable
06
Explain your project decisions during technical discussions and interviews
Course curriculum
A learning progression that moves from foundation to project work.
Each module builds on the previous one, helping you connect concepts instead of learning isolated topics.
Module 01
Python for Data
Python fundamentals • NumPy • Pandas • Jupyter workflow
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Python fundamentals
NumPy
Pandas
Jupyter workflow
Data structures
Module 02
Data Preparation
Data cleaning • Missing values • Feature preparation • Data transformation
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Data cleaning
Missing values
Feature preparation
Data transformation
Exploratory analysis
Module 03
Data Visualization
Visual analysis • Charts and plots • Business interpretation • Data storytelling
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Visual analysis
Charts and plots
Business interpretation
Data storytelling
Dashboard concepts
Module 04
Machine Learning Foundations
Supervised learning • Regression • Classification • Training and testing
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Supervised learning
Regression
Classification
Training and testing
Evaluation metrics
Module 05
Applied AI Concepts
AI application workflows • Model integration • Prompt and model fundamentals • Responsible AI concepts
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AI application workflows
Model integration
Prompt and model fundamentals
Responsible AI concepts
Practical use cases
Module 06
Data Science Capstone
Problem definition • Data preparation • Model development • Evaluation
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Problem definition
Data preparation
Model development
Evaluation
Presentation of results
Career direction
Connect your learning to real technical roles.
Career readiness comes from fundamentals, implementation quality, project evidence, communication and continuous practice — not course completion alone.
Skills employers expect you to discuss
PythonPandasMachine LearningAI
Course completion supports learning and portfolio development, but employment depends on individual skills, interview performance, current opportunities and employer selection.
Compensation varies by role, location, portfolio quality, interview performance and professional experience. Instead of promising a fixed salary, CISS training focuses on practical skills, project evidence and interview readiness that can strengthen your profile.
Certificate preview
CISS IT Training
Certificate of completion
Data Science & AI
Awarded to
Learner Name
Course completion
Course completion
Complete your Data Science & AI learning journey with a professional course certificate.
Certification is tied to completing the required learning work and applicable practical evaluation for the selected course.
Complete the required course learning modules.
Finish applicable practical assignments and implementation work.
Complete applicable project evaluation where included.
Receive a CISS IT Training course completion certificate.
Course enquiry
Questions about the Data Science & AI course?
Share your current experience and learning goal. Our training team can help you understand the curriculum, practical projects, certification, training mode and available batches.
Course selection guidance
Learning path discussion
Batch and training details
Project and certification guidance
Emailtraining@cissittraining.com
Training SupportCourse & batch guidance
Course enquiry
Tell us what you want to learn.
Choose your course interests, add your contact details and share your learning goal.
Course FAQs
Clear answers before you choose your learning path.
Review the most common questions about course structure, practical learning, certification and training support.
01Who should join the Data Science and Applied AI course?
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This course is designed for students, graduates and professionals who want structured, practical training in Data Science & AI. The recommended starting level is intermediate.
02What is the duration of the Data Science and Applied AI course?
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The current planned duration is 6 months. Actual schedules may vary by batch, learning mode and training calendar.
03Will I work on practical projects?
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Yes. Practical assignments and project development are part of the learning process. This course currently includes a project-focused structure with approximately 6 guided project or implementation milestones.
04Is placement assistance included?
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Career preparation support may include resume review, portfolio guidance, interview practice and opportunity guidance. Placement assistance supports preparation and does not guarantee employment.
05Do I receive a certificate?
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Learners who complete the required course work, assignments and applicable project evaluation can receive a course completion certificate from CISS IT Training.
Start your learning journey
Ready to build practical Data Science & AI skills?
Talk to the CISS IT Training team about the curriculum, batch availability, training mode and a suitable starting level.