Best Advanced Data Science Course in Delhi
Learn Python, Machine Learning, Deep Learning & AI
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Best Data Science Course in Delhi – Learn Python, Machine Learning, Deep Learning & AI
If you have been comparing institutes for a data science course in Delhi, you already know the field is crowded with jargon, half-finished tutorials, and courses that promise a lot but deliver very little hands-on practice. At Anshika Digital Media, we built our Data Science program around one simple idea: you should leave the classroom knowing how to write Python code, build machine learning models, train deep learning networks, and apply artificial intelligence to real business problems — not just recognise the buzzwords on a slide.
Whether you are a fresh graduate, a working professional planning a career switch, or someone exploring data science out of pure curiosity, this course is designed to take you from zero coding background to a confident, job-ready data scientist.
Located near Saket Metro Station in New Delhi, our institute combines structured classroom learning with live, client-based projects, so every concept you study is immediately tied to a practical use case. Read on to understand exactly what the course covers, how the batches are structured, and how our placement team supports you once your training is complete.
Why Choose Anshika Digital Media?
Industry-Experienced Trainers
Trainers who have actually built and deployed data science and AI solutions, not just taught from a textbook.
Project-First Teaching Style
Every module ends with a hands-on assignment or a mini-project so the concept sticks.
Small, Focused Batches
Morning, afternoon, evening, and weekend slots so professionals and students attend comfortably.
Live, Client-Based Projects
Projects mirroring real business problems instead of recycled textbook datasets.
One-on-One Doubt-Clearing
Sessions dedicated to complex concepts like gradient descent or backpropagation.
ISO & MSME Certified
An ISO-certified, MSME-registered training institute with a decade of educational experience.
What Is Data Science, and Why Is Everyone Talking About It?
In simple terms, data science is the discipline of using programming, statistics, and mathematical reasoning to find patterns inside data and turn those patterns into decisions. Every time you get a personalised recommendation on an app, see a fraud alert from your bank, or read about a self-driving car avoiding an obstacle, there is a data science process working quietly in the background — usually built on Python, statistical modelling, and machine learning.
The demand for skilled data scientists has grown for a straightforward reason: companies are collecting more data than they know what to do with, and very few people can actually translate that raw data into a working model or a useful prediction. This is exactly the gap our Data Science course in Delhi is designed to fill. You do not need a background in computer science or advanced mathematics to start — our curriculum begins from the fundamentals and gradually builds up to advanced machine learning, deep learning, and AI concepts, so a complete beginner and a working IT professional can both learn at a pace that suits them.
Batch Details & Course Structure
We understand that students and working professionals both join this course, which is why batch timings and learning modes are kept highly flexible.
| Course Detail | Information |
|---|---|
| Course Duration | 6–8 Months (Live, Job-Oriented Training) |
| Mode of Learning | Online & Offline Classroom Training (Saket, New Delhi) |
| Batch Timing | 1.5 Hours per Session – Morning, Afternoon & Evening Slots |
| Fee Structure | One-Time Payment & Easy EMI Options Available |
| Certification | ISO-Certified Data Science Course Completion Certificate |
| Placement Support | 100% Job Placement Assistance with Paid Internship |
Data Science Course Curriculum
Our curriculum is built module by module, with each stage feeding directly into the next. By the end of the program, you will have hands-on experience across the four pillars recruiters look for.
- Learn Python syntax, variables, data types, loops, functions, and object-oriented programming basics.
- Quick start into the libraries that matter most for data: NumPy for numerical computing, Pandas for data cleaning and manipulation.
- Data visualization using Matplotlib and Seaborn.
- Practice importing raw datasets, cleaning, and exploring them visually to draw initial insights entirely in Python.
Hands-on: Importing, cleaning, and visualizing a raw messy dataset
- Descriptive statistics: mean, median, mode, variance, and standard deviation.
- Probability theory, probability distributions, and hypothesis testing.
- Correlation analysis to measure statistical relationships.
- Basic linear algebra and calculus concepts mapped to algorithm mechanics.
- Taught in a practical, applied way to understand model behavior rather than abstract equations.
- Handling missing values, duplicate rows, inconsistent formatting, and outliers.
- Data cleaning and transforming techniques using Pandas and NumPy.
- Feature scaling and encoding categorical variables for model readiness.
- Identifying hidden patterns and statistical anomalies through Exploratory Data Analysis (EDA).
Project: Comprehensive Exploratory Data Analysis (EDA) on a business dataset
- Supervised learning algorithms: linear regression, logistic regression, decision trees, random forests, and support vector machines (SVM).
- Unsupervised learning techniques: k-means clustering and dimensionality reduction.
- Practical ML workflows: train-test splitting, cross-validation, and hyperparameter tuning.
- Evaluating models using core metrics: accuracy, precision, recall, and confusion matrix.
Project: Training, tuning, and evaluating predictive classification and regression models
- Fundamentals of artificial neural networks (ANNs) and activation functions.
- Understanding forward propagation, backward propagation, and gradient descent.
- Convolutional Neural Networks (CNNs) for image-based tasks and classification.
- Recurrent Neural Networks (RNNs) for sequential and time-series data analysis.
- Focus on building and training real networks rather than just memorizing diagrams.
Project: Building and training CNN/RNN neural network models
- Study how machine learning and deep learning power real-world AI applications.
- Building Recommendation Systems, Natural Language Processing (NLP) solutions, and chatbot basics.
- Work on AI-driven mini-projects simulating issues that companies ask data scientists to solve.
- Implement the complete pipeline — from raw data to a working, intelligent application.
Project: Developing a movie/product Recommendation Engine or NLP Sentiment tool
- Apply Python, statistics, machine learning, deep learning, and AI in a single end-to-end project.
- Themes include sales and demand forecasting, customer segmentation using clustering, and image classification.
- Each project is individually mentored to ensure you can defend every design decision confidently in job interviews.
- Creates a robust professional portfolio that gives concrete proof of your skills beyond a certificate.
Portfolio Capstone: End-to-end individually mentored industry dataset project
Tools & Technologies You Will Master
By the end of the program, you will have practical, project-tested experience with the following tools and libraries, all taught within the Python ecosystem:
Python
Core and Advanced Programming
NumPy
Numerical & Array-based Computing
Pandas
Data Cleaning, Transformation & Analysis
Matplotlib & Seaborn
Data Visualisation & Charting
Scikit-learn
Machine Learning Algorithms & Pipelines
TensorFlow & Keras
Deep Learning & Neural Networks
Applied AI Frameworks
Real-world Predictive & Intelligent Apps
Who Can Join This Data Science Course?
One of the most common questions we get is whether a non-technical background is a problem. It is not.
Graduates & Students
Graduates and final-year students from any stream — engineering, commerce, science, or arts.
Working Professionals
From IT, finance, marketing, or operations who want to transition into a data-driven role.
Entrepreneurs
Business owners looking to use data, machine learning, and AI to make better decisions.
Absolute Beginners
With zero coding experience, since the course starts from basic Python foundations.
Career Support & Placement Assistance
A course is only as valuable as the career outcome it leads to, and this is the area where we invest the most attention.
Once you complete the Advanced Data Science course, our placement team works with you directly on building resumes, preparing portfolios, and arranging mock interviews.
This is also why Anshika Digital Media has been able to maintain a 100% job placement record for students who complete the course requirements — the support does not stop at the certificate; it continues until you are actually placed.
Our Placement Roadmap
- Resume and LinkedIn profile building tailored specifically for data science, ML, and AI roles.
- Portfolio creation using capstone and live projects completed during the course.
- Mock interviews and scheduling with our hiring partners and client network.
- Paid internship opportunities that let you apply your skills on real projects.
- Continued mentorship even after placement for the first few months on the job.
Career Roles You Can Apply For After This Course
Because the curriculum covers Python, statistics, machine learning, deep learning, and AI together, you are not limited to a single job title once you finish the program.
Data Scientist
Building predictive models and turning business questions into data-driven answers.
Machine Learning Engineer
Designing, training, and deploying ML models into production systems.
Data Analyst with Python
Analysing structured datasets and presenting insights using Python-based tools.
AI / Deep Learning Engineer
Working on neural networks, computer vision, and NLP-driven applications.
Junior Research Analyst
Supporting data-backed decision-making for product, marketing, or finance teams.
Many students also use the skills from this course to take on freelance data science projects or build their own AI-powered tools and products, especially after completing the capstone project.
Key Skills You Will Walk Away With
Beyond the syllabus, here is a practical summary of the abilities you will have once you finish this Data Science course in Delhi:
Writing clean, efficient Python code to load, clean, and analyse real-world datasets.
Applying statistical thinking to validate whether a pattern in data is meaningful or just noise.
Building, training, and evaluating machine learning models for classification, regression, and clustering problems.
Designing and training deep learning models, including CNNs and RNNs, for image and sequence-based tasks.
Translating an open-ended business problem into a structured AI or machine learning solution.
Presenting data-driven findings clearly, through visualisations and a portfolio of completed projects.
Why Data Science Is a Smart Career Choice for Delhi Students
Delhi-NCR is home to one of the largest concentrations of IT companies, startups, and analytics teams in the country, which means demand for skilled data scientists in the region is consistently high. Companies across banking, e-commerce, healthcare, logistics, and ed-tech are actively hiring professionals who can work with Python, build machine learning models, and apply AI to solve business problems. Choosing a structured, project-based data science course in Delhi — rather than relying only on scattered online tutorials — gives you a clear, guided path into this growing job market, along with the kind of mentorship and placement support that self-study simply cannot offer.
Beyond the immediate job market, data science skills also age well. Unlike narrow tool-specific skills that can become outdated within a few years, the foundation you build here — Python programming, statistical reasoning, machine learning, and neural network design — stays relevant as new AI tools and frameworks emerge, because you understand the underlying logic rather than just the interface of a single software product. That is precisely why we structure the course around core concepts and hands-on coding rather than around any one trending tool, so the skills you graduate with continue to be useful years into your career.
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Frequently Asked Questions
Find answers to common questions about the Advanced Data Science Course, eligibility, batches, and placements.
No. The course begins with Python fundamentals, so students with zero prior coding experience are able to follow along comfortably before moving into machine learning, deep learning, and AI. Most batches include a mix of complete beginners and working professionals, and trainers pace each module so neither group feels left behind.
The course typically runs for 6 to 8 months, depending on your batch and learning pace, with each session lasting around 1.5 hours. This duration is intentional — it gives enough time to genuinely absorb Python, statistics, machine learning, and deep learning, instead of rushing through advanced topics in a few crash-course weeks.
Yes. You can choose between online classes or offline, in-person training at our institute near Saket Metro Station in New Delhi, depending on what is more convenient for you.
Yes. The course includes hands-on assignments, live client-based projects, and a final capstone project, so you finish the program with a practical portfolio, not just theoretical knowledge.
The curriculum specifically includes dedicated modules on Machine Learning, Deep Learning, and Artificial Intelligence, alongside Python and statistics, so you are trained on advanced, in-demand skills rather than just introductory data handling.
Yes. We offer 100% placement assistance, which includes resume building, portfolio support, mock interviews, and paid internship opportunities to help you transition smoothly into a data science role.
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