4.9★
AI-InfusedData Science with Agentic AI course in Delhi
15 MonthsOffline
Next batch 17 Nov 2026
Free LMS · 1 yrPlacement supportNo-cost EMI
Best SellingAI-InfusedAdvanced Data Science
Advanced Data Science Course in Delhi with Gen AI
Looking for the best Data Science Course in Delhi with Gen AI? Brillica Services offers a job-focused Data Scientist Course in Delhi designed for students, beginners, and business owners. This course helps you learn practical data science skills using Python, SQL, Machine Learning, Deep Learning, MLOps, AWS, and Generative AI. With hands-on projects, expert trainers, and placement assistance, you can build industry-relevant skills and prepare for career opportunities in data science and AI.
Duration12 Months
ModeOffline
Next batch17 Nov 2026
PaymentNo-cost EMI
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Highest package offered ₹15 LPA4.8★Google rating4.9★Justdial rating20,000+ learners trained2,000+ placed
Program highlights
Build Industry-Ready Skills with Practical Training
12 MonthsStructured classroom training
DelhiLearn in person
1 yearFree BrillicaNext LMS access
15PDP & interview sessions
100%Placement assistance
0%No-cost EMI available
AI-Infused Courses
Build industry-relevant skills with modern AI tools and technologies integrated into your learning experience.
Free LMS for 1 Year
Access class recordings, study notes, quizzes, assignments, and projects on BrillicaNext for 12 months to support continuous learning.
BrillicaNext Mobile App
Stay connected to your learning journey with convenient mobile access to course resources on Android and iOS.
Placement Support
Prepare for career opportunities with resume building, LinkedIn profile guidance, mock interviews, and placement assistance.
No-Cost EMI
Make your learning journey more accessible with convenient monthly instalments through available EMI options, subject to applicable terms.
Curriculum
Explore the Course Curriculum
- Data fundamentals and the pillars of data analytics
- Data Analytics vs Data Science
- Machine Learning, AI and Generative AI explained
- Data science lifecycles and workflows
- Roles and career paths in data science
- DBMS vs RDBMS, MySQL / PostgreSQL setup
- SQL command types: DDL, DML, DQL, DCL, TCL
- Data types, schemas, CRUD and loading data
- SELECT, aliases, LIMIT/OFFSET, DISTINCT
- WHERE, BETWEEN, LIKE, REGEXP and sorting
- Text, date-time, NULL and CAST functions
- GROUP BY, HAVING, WITH ROLLUP
- CASE statements and pivoting with CASE WHEN
- Set operations, constraints, keys and normalization (1NF–3NF)
- ER diagrams; inner, outer, cross, self and anti-joins
- Nested and correlated subqueries, EXISTS / ANY / ALL
- Chaining multiple CTEs
- Window functions: ROW_NUMBER, RANK, LAG, LEAD, running totals
- Views, stored procedures, temp tables, indexes and EXPLAIN
- Exporting results; MySQL with Python (pandas.read_sql)
- Setup, Jupyter Notebook, comments and variables
- Data types, type casting, input and operators
- Importing modules: random, math, datetime
- Strings, lists, tuples, sets and dictionaries
- Indexing, slicing, functions and methods
- Comprehensions and generator expressions
- Conditionals, ternary operator, loops, break/continue
- Functions, *args/**kwargs, scope (LEGB) and recursion
- Lambda and higher-order functions: map, filter, reduce, zip
- User-defined modules, packages and pip
- File handling: text, CSV and JSON
- Exception handling and custom exceptions
- Classes, objects, constructors and self
- Instance, class and static methods
- Encapsulation, inheritance, polymorphism, abstraction
- NumPy array creation, attributes and random module
- Indexing, reshaping, stacking and splitting
- Vectorisation, broadcasting and np.where / np.select
- Series and DataFrames; reading CSV, Excel, JSON and SQL
- Selection with loc / iloc, filtering and sorting
- Missing values, duplicates, string cleaning and apply()
- Binning, outlier treatment (IQR), GroupBy and agg()
- Pivot tables, crosstab, melt, merge and join
- Date-time handling, resampling and rolling windows
- Matplotlib: line, bar, area, pie, scatter and distribution charts
- Customisation, subplots and styles
- Seaborn: categorical, distribution, relational and matrix plots
- Univariate, bivariate and multivariate analysis
- Correlation, outliers and missing-value patterns
- Notation (Σ, Π, sets), functions and graphs
- Exponents, logarithms and power transformations
- Vectors, norms, dot product and cosine similarity
- Matrices, inverse, determinant, rank and vector spaces
- Eigenvalues, eigenvectors, SVD, covariance matrix and PCA
- Limits, derivatives, partial derivatives and gradients
- Chain rule — the foundation of backpropagation
- Loss functions, gradient descent and learning rate
- Entropy, information gain and cross-entropy
- Population vs sample, data and variable types
- Central tendency, dispersion, percentiles, skewness and kurtosis
- Z-scores, normal distribution, Q-Q plots and normality tests
- Log, Box-Cox, Yeo-Johnson and quantile transforms
- Standardisation, min-max and robust scaling
- Counting, conditional probability and Bayes' theorem
- PMF, PDF, CDF and key distributions (Binomial, Poisson, Normal, t, Chi-Square, F)
- Sampling, Law of Large Numbers and Central Limit Theorem
- Estimation, MLE and confidence intervals
- Hypothesis testing, p-values, errors, power and effect size
- Z / t-tests, ANOVA, Chi-Square and non-parametric tests
- Correlation vs causation, bootstrap and Monte Carlo
- A/B testing and experimental design
- SciPy and Statsmodels on real-world datasets
- Garbage in, garbage out and the CRISP-DM workflow
- Features vs target and types of ML problems
- Automated profiling with ydata-profiling and Sweetviz
- Cardinality, constant and correlated features
- Target-driven analysis and feature interactions
- Missingness mechanisms (MCAR, MAR, MNAR) and imputation
- Outlier engineering with Isolation Forest and LOF
- Categorical encoding and high-cardinality handling
- Multicollinearity (VIF), scaling and domain features (RFM)
- Feature selection: filter, wrapper and embedded methods
- Imbalanced data: SMOTE, ADASYN and class weights
- Data leakage, splits, cross-validation and Scikit-learn pipelines
- Types and categories of ML algorithms
- Problem formulation, overfitting and the bias-variance trade-off
- Simple, multiple and polynomial regression
- Ridge, Lasso and Elastic Net; MAE, RMSE, R²
- Logistic regression, KNN, Naive Bayes, SVM and decision trees
- Confusion matrix, precision, recall, F1 and ROC-AUC
- Random Forest, AdaBoost, GBM, XGBoost, LightGBM, CatBoost, stacking
- Cross-validation, Optuna tuning and model selection
- K-Means, hierarchical, DBSCAN and GMM clustering
- PCA, t-SNE, UMAP, anomaly detection and recommenders
- ARIMA, SARIMA, Holt-Winters and Prophet
- SHAP, PDP / ICE and end-to-end pipelines
- Kaggle: Titanic, House Prices, Spaceship Titanic
- DevOps vs MLOps and maturity levels
- Batch vs real-time inference; canary and blue-green deployment
- Modular project structure and environments
- Config, logging, type hints, pytest and data validation
- Git and GitHub workflows for ML
- MLflow experiment tracking and model registry
- DVC data versioning; Pickle, Joblib and ONNX
- Streamlit and Gradio apps
- FastAPI ML APIs with Pydantic
- Docker, Docker Compose and Kubernetes basics
- GitHub Actions, Airflow and Prefect
- Deploying on Render, Hugging Face, AWS, Azure and GCP
- Prediction logging, Prometheus and Grafana
- Data and model drift with Evidently AI
- Perceptron, MLP, forward propagation and activations
- Loss functions and backpropagation from scratch
- Optimisers (SGD, Adam, AdamW) and initialisation
- Schedulers, dropout, batch norm and tuning
- TensorFlow, Keras callbacks and TensorBoard
- PyTorch tensors, autograd and training loops
- CNNs, data augmentation and famous architectures
- Object detection with YOLO and image segmentation (U-Net)
- RNN, LSTM, GRU, Seq2Seq and attention
- Transformer architecture and Vision Transformers
- Autoencoders, VAEs, GANs and diffusion models
- ONNX, quantisation and TensorFlow Lite
- NLP workflow, text collection and regex for NLP
- NLTK, spaCy, TextBlob, Gensim and Hugging Face
- Cleaning, tokenisation, stemming and lemmatisation
- POS tagging, dependency parsing and Hinglish / Indian-language text
- Bag of Words, N-grams, TF-IDF and text similarity
- Text classification, NER and topic modelling (LDA, NMF)
- Word2Vec, GloVe, FastText and Sentence-BERT
- LSTM / BiLSTM text models and Seq2Seq translation
- Subword tokenisation, BERT family, GPT, T5 and BART
- Hugging Face fine-tuning, summarisation and QA systems
- BLEU, ROUGE, METEOR and perplexity
- How LLMs are trained and aligned (SFT, RLHF, DPO)
- Generation parameters and the LLM landscape
- OpenAI, Anthropic and Gemini APIs; structured outputs
- Running open-source LLMs with Ollama; tokens, cost and latency
- Prompt patterns, chain-of-thought and templates
- Managing system prompts, history and memory
- Vector databases: FAISS, ChromaDB, Pinecone, Qdrant
- Chunking, hybrid search, re-ranking and GraphRAG
- RAG evaluation with RAGAS
- LangChain and LlamaIndex
- LoRA / QLoRA fine-tuning; multimodal models, Whisper, Stable Diffusion
- Gen AI-assisted EDA, data cleaning and code generation
- Text-to-SQL and natural-language analytics
- Synthetic data generation and LLM-based data labelling
- Chatbots and copilots with Streamlit and Gradio
- Multimodal apps: vision-language models, speech and image generation
- Cost, latency and quality optimisation for Gen AI apps
- LLM evaluation, guardrails and responsible AI
- LangSmith / Langfuse, FastAPI, Docker and vLLM serving
Tools & technologies
Master Industry Tools Through Hands-On Practice
Pandas
Python
Numpy
SQL
Tensor Flow
AWS
Matplotlib
Scikit Learn
Gen AI
PyTorchProjects
Build Real Projects. Showcase Your Skills
Project 01
Car's Ex-Showroom Price Prediction
Predict car ex-showroom prices using machine learning based on features, specifications, and brand.
Project 02
Kidney Stone Classification Project
Classify kidney stone cases using medical data and machine learning classification techniques.
Project 03
Brain Tumor Detection Using MRI Scan Images
Detect brain tumors from MRI scan images using image processing and deep learning models.
Project 04
Casting Iron Defect Image Classification
Identify casting iron defects from images using computer vision and deep learning techniques.
Project 05
SPAM Detection
Classify messages or emails as spam or legitimate using natural language processing and machine learning.
Project 06
Recommendation System
Recommend relevant products or content based on user preferences, behavior, and historical data.
Certification
Earn an industry-recognised certificate
Showcase your skills and project experience with a Brillica Services certificate. Add it to your resume and LinkedIn profile to highlight your achievements, strengthen your professional credibility, and stand out to potential employers.
- Worldwide RecognitionShowcase your course completion and practical skills with a certificate from Brillica Services to support your professional profile when applying for opportunities.
- Lifetime ValidityYour certificate remains valid for a lifetime, allowing you to highlight your learning achievement throughout your career.
- Project-Based AchievementEarn your certificate by completing course requirements, projects, and assessments, demonstrating your practical learning beyond classroom attendance.
Career outcomes
Our learners work at top companies
Our placement team prepares you for career opportunities across industries with expert guidance, interview preparation, and job-readiness support.
Data ScientistML EngineerAI EngineerData AnalystGenAI DeveloperNLP Engineer
Who should join
Built for Delhi NCR's beginners and professionals who want a career in Data Science and AI
- Graduates and final-year students (B.Tech, BCA, MCA, B.Sc) in Delhi who want a first job in data science or AI.
- Software developers and testers moving into data science, machine learning and AI engineering.
- Data and business analysts who want to add Python, machine learning and Gen AI to their skills.
- Working professionals and career switchers who want a structured classroom path into AI.
- Founders and freelancers who want to use AI and data to automate work and decisions.
Mentors
Learn from Industry Experts
Prashant SinghSr. Training ConsultantEXP 14+ yrs
Alumni
Recently placed Brillica learners
Pankaj BhandariSr. Data Analyst
Placed at
Sahil SinhaData Breach Analyst
Placed at
Kanishka GuptaData Analyst
Placed at
Shreya SaranData Scientist
Placed at
Brillica Job-Readiness Program · included free
Skills open the door. Confidence gets you the job.
Alongside your regular course, every Brillica learner goes through our Job-Readiness Program and Personal Development Program (PDP). Resume, communication, GD, aptitude, interview skills and mock interviews, until you're ready to crack the interview.
15+PDP sessions per program
10Job-readiness modules
1:1Resume & mock interview reviews
₹0Extra cost
Resume building
One-on-one resume reviews with ATS-friendly templates for your target role.
Recruiter-ready resumeLinkedIn & portfolio
Optimised LinkedIn profile, GitHub, Behance or campaign portfolio from your course projects.
Profile that gets foundCommunication skills
Spoken English, email writing, presenting your projects and speaking with confidence.
Clear, confident speakingGroup discussion (GD)
Weekly GD rounds on tech, business and current topics with feedback on structure and clarity.
Clear the GD roundAptitude & reasoning
Quantitative, logical and verbal practice in the format used by campus and off-campus drives.
Pass screening testsFees & EMI
Invest in your career, pay monthly
Festive offer · up to 30% offProgram feeAsk for this month's priceAlready counselled? Pay online securely →
No-cost EMI0% interest
Free LMS + BrillicaNext app1 year
Placement supportIncluded
Interview PreparationMock interviews and career guidance
What's included
- Live classroom or online classes
- AI-infused curriculum & tools
- BrillicaNext LMS & app for 1 year
- Projects with mentor reviews
- Job-Readiness Program: resume, GD, mock interviews
- Placement drives & referrals
- Industry-recognised certificate
About the program
About Advanced Data Science Course in Delhi with Gen AI
Every business today uses data to understand customers, improve performance, and make better decisions. Data Science helps turn large amounts of information into useful insights, while Generative AI opens new ways to create intelligent applications and automate tasks. Learning these skills can help you prepare for opportunities in analytics, machine learning, and artificial intelligence.
Brillica Services offers a Data Science Course in Delhi with Gen AI for students, fresh graduates, beginners, and working professionals. This 12-month programme covers Python, SQL, statistics, data analysis, Machine Learning, Deep Learning, and Generative AI concepts. Through guided training, practical exercises, real-world projects, and expert support, you can develop job-relevant technical skills. The course also includes 100% placement assistance to help you prepare for interviews and explore relevant job opportunities.
Whether you are searching for the Best Data Science Course in Delhi, a practical Data Scientist Course in Delhi, or online and classroom training options, Brillica Services can help you understand the available learning paths.
Why Choose Brillica Services for a Data Science Course in Delhi with Gen AI?
Choosing the right Data Science Institute in Delhi involves more than comparing course fees. You should also consider the curriculum, practical training, learning support, project work, and career preparation.
Brillica Services offers a structured learning programme designed to help you understand data science concepts and apply them through practical exercises.
Structured Learning Path
Learn foundational concepts before progressing to data analysis, machine learning, and Generative AI topics. This approach helps you build your knowledge step by step.
Practical Training and Projects
Apply the concepts covered during training through coding exercises, case studies, and projects. Practical work can help you understand how data science techniques are used to solve problems.
Online and Classroom Classes
Choose online or offline learning according to your preferences and available batches. Learners who prefer in-person training can visit the Tagore Garden centre in Delhi.
Flexible Fee Options
The course fee ranges from ₹40,000 to ₹85,000. No-cost EMI options are available, subject to the applicable payment terms. Contact the admissions team for the current fee and payment details.
Career Preparation and Placement Assistance
Receive placement assistance to help you prepare for recruitment opportunities. Career support can include resume guidance, interview preparation, and assistance with exploring relevant job openings.
Data Science Course in Delhi with Gen AI: Duration and Fees
If you are comparing Data Science courses in Delhi, understanding the duration and fee structure can help you plan your learning.
Course Detail | Information |
|---|---|
Course Name | Data Science Course in Delhi with Gen AI |
Course Duration | 12 months |
Course Fees | ₹40,000–₹85,000 |
Core Topics | Python, SQL, Statistics, Data Analysis, Machine Learning, Generative AI |
Learning Method | Practical exercises, guided training, and projects |
Payment Option | No-Cost EMI |
Learning Mode | Online and Offline |
Training Centre | Third Floor, BF-1, Block Bf Tagore Garden Rd, near Metro Station, Block BF, Tagore Garden, Tagore Garden Extension, Delhi, New Delhi, Delhi 110027 |
Career Support | 100% placement assistance |
The Data Science Course Fees in Delhi at Brillica Services range from ₹40,000 to ₹85,000. The applicable fee depends on the selected programme and current offer. No-cost EMI options are available under applicable terms.
Contact the admissions team to confirm your exact fee, EMI conditions, batch schedule, and admission requirements before enrolling.
[088821 40688: Get Course Fee Details]
What Will You Learn in Our Data Science Course with Gen AI?
A Data Science Course with Gen AI combines core data science concepts with modern AI applications. It helps learners understand how data can be collected, processed, analysed, and used to develop intelligent solutions.
At Brillica Services, the programme covers foundational and advanced concepts through a structured curriculum.
1. Python Programming
Learn Python fundamentals, variables, data types, functions, loops, and other essential programming concepts. Python is widely used for data analysis, automation, machine learning, and AI development.
2. SQL and Database Management
Understand how to store, retrieve, filter, and manage information in databases. Learn SQL concepts that help you work with structured data and prepare it for analysis.
3. Statistics and Mathematics
Build an understanding of probability, descriptive statistics, data distributions, and other mathematical concepts used in data analysis and predictive modelling.
4. Data Analysis and Visualisation
Learn how to organise, clean, and analyse datasets using tools such as NumPy and Pandas. Explore visualisation libraries such as Matplotlib and Seaborn to present findings through charts and graphs.
5. Machine Learning
Understand supervised and unsupervised learning, model training, feature selection, and model evaluation. Explore how machine learning can support tasks such as classification, forecasting, and customer segmentation.
6. Deep Learning and Natural Language Processing
Explore the fundamentals of deep learning and Natural Language Processing (NLP). Understand how AI models can work with text, images, and other forms of data.
7. Generative AI and Large Language Models
Learn the basic concepts behind Generative AI, large language models (LLMs), prompt engineering, and AI-powered applications. Explore use cases such as text summarisation, question-answering systems, and chatbots.
8. Practical Projects and Case Studies
Apply your learning through practical exercises and data-related projects. Project work can help you understand how technical concepts are used to solve business problems and build a portfolio for career preparation.
Tools and Technologies Covered in the Data Science Course in Delhi
The Data Science Course in Delhi with Gen AI introduces tools and technologies used in programming, data analysis, machine learning, and AI application development.
Depending on the curriculum and batch, these may include:
Programming: Python
Database: SQL and MySQL
Data analysis: NumPy and Pandas
Data visualisation: Matplotlib and Seaborn
Machine Learning: Scikit-learn
Deep Learning: TensorFlow or PyTorch
Development environment: Jupyter Notebook
Generative AI: Large language model concepts, prompt engineering, and relevant AI tools
Learning these technologies can help you understand different stages of a data science workflow, from preparing data to developing and evaluating models.
Who Can Join Our Data Science Course in Delhi with Gen AI?
The programme may suit learners from different educational and professional backgrounds who want to develop skills in Data Science and Artificial Intelligence.
Students and Fresh Graduates
Students and fresh graduates can build foundational knowledge in programming, data analysis, and machine learning while exploring technical career paths.
Beginners
If you are new to data science, structured training can help you understand core concepts before moving towards advanced topics. Confirm the current admission requirements with Brillica Services before enrolling.
Working Professionals
Professionals working in IT, finance, marketing, operations, and related fields can explore data science and AI skills to support their professional development.
Career Switchers
If you want to move towards a data-focused or technology-related career, learning Python, SQL, data analysis, and machine learning can help you begin developing relevant skills.
Business Owners and Managers
Business owners and managers can explore how data analysis and AI applications support customer research, performance monitoring, planning, and decision-making.
What Are the Eligibility Requirements for a Data Science Course in Delhi?
Data Science involves programming, logical reasoning, statistics, and problem-solving. Having a background in mathematics, computer science, statistics, or a related field can be helpful.
However, the exact admission criteria depend on the current programme requirements. If you are a beginner or have a non-IT background, contact Brillica Services to confirm the eligibility conditions and whether the course starts with foundational concepts.
Before enrolling, make sure the course matches your current skill level, learning goals, and career plans
Career Opportunities After a Data Science Course in Delhi with Gen AI
Data Science and Generative AI skills can be relevant to several technical and analytical career paths. The role you pursue will depend on your knowledge, project experience, portfolio, and employer requirements.
Data Scientist
Analyse datasets, identify patterns, apply statistical methods, and develop models that help businesses make informed decisions.
Data Analyst
Prepare reports, examine business data, identify trends, and communicate insights to support decision-making.
Machine Learning Engineer
Help develop, test, evaluate, and improve machine learning models for practical applications.
AI Engineer
Work on AI-powered applications using machine learning, deep learning, and related technologies.
Business Intelligence Analyst
Use data and reporting tools to track business performance and present findings through reports and dashboards.
Generative AI Developer
Explore the development of applications that use large language models for tasks such as question answering, content generation, and summarisation.
Other possible paths may include NLP-related roles, data engineering, and research-focused positions. Some jobs require advanced technical skills, additional qualifications, or professional experience, so completing a course alone does not guarantee eligibility for every role.
Data Science Course in Delhi with 100% Placement Assistance
Brillica Services provides 100% placement assistance to support learners as they prepare for relevant job opportunities after training. The aim is to help you improve your job readiness and understand the recruitment process.
Career support may include:
Resume preparation and improvement
Project portfolio guidance
Mock interviews and interview preparation
Communication and soft skills development
Career guidance and job application support
Information about relevant hiring opportunities
Placement assistance is intended to support your job search. It does not guarantee employment, a specific salary, or selection by any particular company. Hiring decisions depend on your skills, interview performance, experience, and employer requirements.
Why Learn Data Science in Delhi?
Delhi NCR has a broad business and technology ecosystem that includes IT services, consulting, finance, retail, e-commerce, and startups. Organisations in these sectors use data to understand performance, improve services, and support business decisions.
Learning Data Science in Delhi can help you prepare for opportunities across different industries. A course that combines programming, analytics, machine learning, and Generative AI can also help you explore how these skills are used in modern workplaces.
When selecting a Data Science Training Institute in Delhi, compare the syllabus, practical training, tools covered, project work, course fees, batch timings, and placement assistance before making your decision.
Attend Data Science Classes in Delhi
Brillica Services offers offline Data Science Classes in Delhi at its Tagore Garden centre, along with online learning options.
The centre is located near Tagore Garden Metro Station, making it a convenient option for learners travelling from nearby parts of West Delhi.
Training Centre Address:
Third Floor, BF-1, Block Bf Tagore Garden Rd, near Metro Station, Block BF, Tagore Garden, Tagore Garden Extension, Delhi, New Delhi, Delhi 110027.
Phone: +91 88821 40688
If you are looking for a Data Science Course Near Tagore Garden Metro Station, contact our team to confirm the available classroom batches, timings, fees, and admission process.
FAQs
Advanced Data Science Course in Delhi with Gen AI: FAQs
The Data Science Course in Delhi with Gen AI at Brillica Services has a duration of 12 months. The programme covers data science concepts through structured training, practical exercises, and project work. Contact the admissions team at (088821 40688) to confirm the current batch schedule and class timings.
Yes. Brillica Services provides 100% placement assistance to help learners prepare for relevant job opportunities. Support may include resume guidance, interview preparation, project portfolio development, and career guidance. Placement assistance does not guarantee a job or a particular salary package.
Yes, beginners can enrol in this course. The training starts with foundational concepts such as Python, SQL, mathematics, and statistics before progressing to machine learning, Generative AI, and advanced data science topics.
The course fees range from ₹40,000 to ₹85,000. The applicable fee depends on the selected programme and current offer. No-cost EMI options are available under applicable terms. Contact Brillica Services at +91 88821 40688 to confirm the exact fee and payment conditions.
Yes. No-cost EMI options are available for the course, subject to applicable terms and conditions. Contact Brillica Services to confirm eligibility, payment arrangements, and the terms applicable to your selected programme.
Brillica Services offers structured data science training that combines core data science concepts with Generative AI. Learners gain practical knowledge of Python, SQL, machine learning, data visualisation, and AI tools through guided exercises, projects, and expert support.
After completing the course, you can explore roles such as Data Scientist, Data Analyst, Machine Learning Engineer, AI Engineer, and Business Analyst. Your career opportunities will depend on your skills, practical experience, portfolio, and employer requirements.
Yes, this course can be suitable for working professionals who want to upgrade their technical skills. Contact Brillica Services to check the availability of online, weekend, or other flexible batch options before enrolling.
The course covers Python, SQL, NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, AWS and Generative AI tools. You learn each tool through hands-on exercises and projects, from data analysis and machine learning to deep learning and building AI-powered applications.
Previous coding experience may not be necessary if the programme starts with programming fundamentals. You will learn Python and other core concepts step by step. Contact Brillica Services to confirm the eligibility criteria and whether the course matches your current skill level.
Data Analytics focuses on examining existing data to find insights and support business decisions using tools such as Excel, SQL, and Power BI. Data Science includes these analytical foundations and extends into statistics, predictive modelling, machine learning, and AI. Adding Generative AI introduces skills for building applications such as intelligent chatbots and AI-assisted data solutions.
A Data Science Course in Delhi with Gen AI can help you develop skills in data analysis, machine learning, and modern AI applications. At Brillica Services, you can learn through structured training, practical exercises, case studies, and projects designed to help you apply these technologies to real-world problems.
A Data Science Course with Gen AI may introduce learners to Generative AI concepts, large language models, prompt engineering, and AI-powered applications. Review the detailed syllabus to understand the specific Gen AI topics and practical work included in the programme.
Start your Advanced Data Science Course in Delhi with Gen AI journey
Speak with our counsellor today to explore course fees and secure your admission with no-cost EMI.
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