Computational Thinking and Data Science Training in Gurgaon, Delhi

Computational Thinking and Data Science

Think like a Computer Scientist !!

Duration : 1 year Classes : 72 Days : Weekdays / Weekends

Overview
Curriculum
Pre-requisite
Review

Stop just learning software; start mastering the fundamental thought process behind every technological breakthrough! Our "Computational Thinking and Data Science" course is designed for aspiring innovators, students, and career changers who need to build a rock-solid foundation. You will move beyond memorizing syntax and learn how to think like a data scientist: Decomposing complex problems, identifying patterns, developing algorithmic solutions, and abstracting those solutions for real-world application. Using Python, you will gain hands-on experience translating messy data challenges into elegant, efficient, and machine-executable code. This course is your essential first step toward a career in Data Science, Engineering, or any field demanding analytical rigor.

It is a foundational skill in computer science. Computational thinking is a versatile and powerful approach to problem-solving that can be applied to a wide range of disciplines and everyday situations. It involves decomposing problems, recognizing patterns, abstracting essential details, and developing algorithms to devise effective solutions. It aims to help students, regardless of their Engg major, to feel justifiable confident of their ability to write small programs that allow them to accomplish useful goals. The training will use Python programming language. This program is designed to cultivate a mindset that blends logical reasoning, algorithmic thinking, and data literacy-essential skills for navigating today's digital landscape. Whether you're new to programming or looking to sharpen your analytical edge, this course provides the intellectual toolkit to thrive in any data-centric field.

Target Audience:-
- Students and educators seeking a strong foundation in computational thinking and data literacy
- Aspiring data scientists, analysts, and developers beginning their journey into data science
- Professionals in non-technical roles who want to understand and leverage data in decision-making
- Researchers and academics looking to apply structured thinking to data-driven inquiry
- Anyone curious about how computers and data can be used to solve real-world problems
- Students who want to add Computer Scientist capabilities to their curricular

Learning Outcomes:-
- Decomposition, Pattern recognition, Abstraction, and Algorithm design
- Apply logical and algorithmic reasoning to solve structured and unstructured problems
- Use programming constructs to implement solutions
- Perform statistical analysis and interpret data distributions
- Communicate data-driven insights through visualizations and narratives
- Develop a problem-solving mindset applicable across disciplines and industries

Course Format:-
✔ The course shall be delivered through a combination of lectures, interactive discussions & case studies
✔ Participants are exposed to practical exercises and new-age projects, where they learn by doing
✔ Participants shall have access to online resources, including reading materials, videos & business simulations
✔ Students shall receive all the study material
✔ Guest speakers from the industry may be invited to share insights and experiences
✔ Regular assessments and quizzes will be conducted to reinforce learning
✔ This is a Classroom only training
✔ Corporates: We understand your specific needs and goals. Contact us for customizations to this training

Trainers:-
✔ Equipped with multidisciplinary backgrounds
✔ Experts from the field of Maths, Financial Markets, AIML, Data Science & Management
✔ Each with over 25+ years of International experience working in EU / US / Australia
✔ All our trainers are Highly Qualified and Certified, in their respective subject areas

-Candidate must hold a Bachelors degree with Maths discipline. Students can also apply.
-Candidate is familiar with SQL, Statistics and Python

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NB: All our trainings are always tailored to adopt to the Individual's Pace and Learning Depth.

NB: As a stepping stone, providing foundational knowledge, Bridge Courses are conducted periodically, to help students transition between different levels by closing knowledge gaps. These classes can be attended ad hoc, and are 'complimentary' for our bonafide students.

Kindly fill the DownloadPDF Form for the Brouchre with latest curriculum and full Training details.
Or you may Book an Appointment to collect your Brouchre and complete your registration.

This syllabus provides a structured, module-by-module breakdown of this comprehensive training program focused on participants overall performance, retention, and engagement, covering foundational theory, implementation, best industry practices and advanced techniques in the subject.

Module 1: Introduction to Computational Thinking (CT) and Problem Framing
✔ Core Pillars of Computational Thinking
✔ Decomposition
✔ Data Representation and Abstraction
✔ Introduction to algorithms and flowcharts
✔ Optimization Problems
✔ Three A's and Four R's
✔ Basic Python Setup
✔ Data Types in Practice

Module 2: Pattern Recognition and Data Structuring
✔ Pattern Recognition in Data
✔ Data Structures and Efficiency
✔ Data Abstraction in Pandas
✔ Data Cleaning Patterns
✔ Conditional Patterns

Module 3: Algorithmic Design and Data Processing
✔ Algorithms Defined
✔ Searching and Sorting Algorithms
✔ Algorithmic Complexity (Big O)
✔ Data Transformation Algorithms
✔ Implementing Functions

Module 4: Modeling, Simulation, and Statistical Abstraction
✔ Abstraction in Modeling
✔ Probabilistic Abstraction datasets"
✔ Simple Simulation Design
✔ Statistical Algorithms
✔ Data Visualization as Abstraction
✔ Hypothesis testing and confidence intervals
✔ Correlation vs causation
✔ Linear regression
✔ Confidence Interval
✔ Sampling & Standard Error
✔ Graph-Theory Models
✔ Stochastic Models
✔ Random Models
✔ Monte Carlo Simulation

Module 5: Project Application and Ethical Thinking
✔ >End-to-End Problem Decomposition
✔ Abstraction in Model Evaluation
✔ Algorithmic Bias and Ethics
✔ Reproducibility and Documentation

Module 6: Capstone Project
✔ Choose a real-world problem and dataset
✔ Apply computational thinking to define the problem
✔ Use Python and data science tools to clean, analyze, and model data
✔ Present findings through visualizations and a written report

NB:The curriculum is regularly subjected to updates, reflecting the latest industry trends & current technological advancements.

At Vyom Data Sciences, we aspire to provide the latest curriculum and most recent technology, as a standard component of all our trainings. Experts, with 25+ years of experience from USA, Europe and Australia, bring the best industry practices while designing and executing these trainings. All our trainers are Highly Qualified and Certified in their respective subject areas.

Kindly fill the DownloadPDF Form for the Brouchre with latest curriculum and full Training details.
Or you may Book an Appointment to collect your Brouchre.

Bhawana

Fabulous NLP + ML course

I have eleven plus years of experience taking training courses. I do not usually complete surveys.
Your instructor was excellent, the best I've experienced on a software subject, and I couldn't imagine him doing a better job of seamlessly walking students through a breadth of information for such complex subject like AI and ML. he did a fabulous job pacing everything and addressing student questions. I am very impressed.

Harish

Excellent ML course!

The course was well structured and easy to understand. Good pace of learning.
The institute believes to provide knowledge as well as guidance in detail to each & every student.
I completed my ML course from the institute. Their international exp does help a lot !
Thanks for the training sir.