Executive Certification in Data Science with AI Specialization
A strategic approach to harness Data & AI for Professional Impact!
*TIH Partnerships via Edzor CAITE
1070 Hours
12-15 Months
14 June
Noida
28 June
Gurgaon
29 Mar
Gurgaon
Learning Modes
Classroom Sessions
INR 1,08,560/-*
(Pay in Easy Installments)
INR 88,500/-*
(Pay in Easy Installments)
Interactive Live Online
INR 92,040/-*
(Pay in Easy Installments)
INR 76,700/-*
(Pay in Easy Installments)
Blended eLearning
INR 80,240/-*
(Pay in Easy Installments)
INR 70,800/-*
(Pay in Easy Installments)
Courses Included
Artificial Intelligence Engineering
₹ 20000/-
Artificial Intelligence Engineering
₹ 20000/-
Artificial Intelligence Engineering
₹ 20000/-
₹ 65000/-
₹ 48000*/-
Optional Course
Data Science using R
₹ 20,000
₹ 4000/-
Course Fees
(Program fees starts from)
INR 80,240/-*
(Program fees starts from)
INR 70,800/-*
Course Overview
Course Duration
12-15 Months
Total Student Workload
1070 Hours
Placement Readiness
8 Weeks (Post Certification)
The Executive Certification in Data Science with Artificial Intelligence offers comprehensive mastery across statistics, machine learning, data science, and AI. Data science and AI are transforming business outcomes across healthcare, finance, retail, eCommerce, climatology, and beyond.
Designed for working professionals and aspiring data practitioners, the programme offers flexible learning formats to suit diverse schedules and preferencesi including Instructor-led live online training, Blended e-learning sessions, and Classroom-based instruction in Noida, Gurgaon, and Bangalore.
On completion, you earn dual certification with the IIT Patna Vishlesan I-HUB Foundation & NASSCOM FutureSkills Prime.
In addition, learners gain access to the Placement Readiness Program (PRP): A 2-month post-certification, industry-focused module designed to sharpen technical skills, communication, and problem-solving through interview prep, practice tests, and simulated placement days.
To further strengthen your career prospects, the programme includes a Job Guarantee with 50% Fee Refund: https://www.analytixlabs.co.in/placements/
Course Curriculum
The Executive Certification in Data Science with AI Specialization is a 12–15 month programme spanning 1,070 hours of structured learning, designed to equip professionals with end-to-end expertise across analytics, machine learning, and artificial intelligence.
The core curriculum progresses through three interconnected learning paths:
Data & Analytics Foundation covers data analytics with SQL (MySQL); visual analytics and dashboarding using Power BI; applied data science using Python; and applied statistics with predictive modeling using linear and logistic regression.
Machine Learning & Advanced Analytics equips learners with expertise in predictive modeling, feature engineering, and supervised and unsupervised learning. The module covers industry-standard machine learning algorithms, clustering techniques, deep learning, neural networks, Keras, TensorFlow, and AI-assisted model development.
Generative AI & Agentic Systems builds expertise in generative AI and no-code agentic AI frameworks; covers Python foundations for AI development; and culminates in applied agentic AI systems using Python. An advanced module on computer vision and reinforcement learning completes the specialization.
Throughout the programme, each module combines live sessions, reading materials, assignments, and capstone projects to deliver hands-on mastery across the full data science and AI stack.
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Orientation & Fundamentals of Analytics
Introduction to Analytics & Life Cycle of Data Analytics Projects
- What is Analytics, Data Science, and AI? – Definition
- Difference between Business Analytics, Data Analytics, Data Science vs. AI
- Types of data (Structured vs. Unstructured vs. Semi-structured)
- Understand the impact and use of data analysis based on the real-world examples
- Stages of Analytics (Introduction to types of data analysis – Descriptive vs. Diagnostic vs. Predictive vs. Prescriptive vs. Cognitive)
- Analytics Methodology & problem-solving framework (Steps to solve a Data Analysis problem.) – Life Cycle of Analytics Project
- What is AI, GenAI, Agentic AI?
- The role of AI in Data analytics
- The applications of AI in day-to-day work?
- How is AI changing the roles over time?
- Expectations from the Employers
Data Analytics with SQL(MySQL)
RDBMS - SQL
- Basic RDBMS Concepts (ERD, Data Modeling, Schema, Normalization, ETL, etc..)
- Introduction to MySQL Server
- Overview of SQL Commands (Overview of DDL, DML, DCL, DQL), SQL Syntax basics, Operators, Order of execution etc.
- Data-based objects creation (DDL Commands – Data Gathering – CRUD Operations)
- Data manipulation (DML Commands) & DQL (Data Query), Data Preparation & Analysis (Data Aggregations & Summarizations)
- Accessing data from Single & Multiple Tables using SELECT statement & Clauses, inbuilt functions
- Advanced SQL (Advanced Joins, Subqueries, Window Functions, Views, CTEs, Stored Procedures etc.)
- Integrating SQL for Analytics (Databases & Schema, Python integration)
- AI-Powered SQL & Optimization (AI-Assisted Querying and Optimization)
Visual Analytics & Dashboarding using Power BI
PowerBI
- Introduction to Data Visualization concepts, BI, Power BI
- Data Preparation and Modelling (Power Query) – Extracting data from various sources, Load Data Model – Manage Relationships
- Data Analysis Expressions (DAX)
- Reports Development (Basic & Advanced Visuals in Power BI) – Types of visuals, mapping charts with analysis, and chart formatting
- Data-Driven Story Reports
- Creation of Dashboards – Wire Frames, Slicers, Filters, Tooltips, buttons – KPI-Based Dashboarding – E-commerce Case
- Advanced / Other Power BI Concepts (Parameters, Dynamic measures, Insights presentation etc.)
- Power BI Analytics
- Publishing workbooks and Workspace
- Overview of Power BI Service
- AI-Enhanced Presentations or design of dashboard with ChatGPT/Claude
Foundations of Programming Logic
(Python Core Programming)
- Introduction to Python for Data Science
- Essentials of Python Programming (Environment, IDE’s, syntax rules, objects, indentation, comments, assignment rules, file handling, etc.)
- Data Types (numeric, string, date time, etc.) & Operators-Operands, Expressions
- Data Structures (Lists, tuples, dictionaries, sets) – Accessing Data (Indexing & Slicing)
- In-Built Functions & Methods, Packages
- Conditional, iterative, or Control Flow Statements (if, ifelse, loops, comprehensions, etc.)
- User-Defined Functions (args, kwargs), Lambda functions, Classes
- Error & Exception Handling
- File Handling
- AI-Enhanced Coding Fundamentals – AI-Assisted Coding: Pair Programming with ChatGPT
Python for Data Science
(EDA + Visualization)
- Python Packages for Data Analytics & Data Science
- Operations with NumPy (Numerical Python) – Operations
- Mastering data with Pandas
- Reading (handling diverse data formats), Auditing, Cleansing, Preparing Data with Python & packages (numpy, pandas, datetime, regex, etc.), core techniques in data wrangling (basic & advanced)
- Python-SQL integration to extract data – performing SQL codes in Python
- Data Analysis (EDA (Descriptive, Diagnostic) – statistical analysis) using Python & packages (numpy, pandas, datetime, regex, etc.)
- Data Visualization using Python & packages (matplotlib, seaborn, etc.)
- AI-assisted coding – AI-Powered Data Wrangling with PandasAI
Applied Statistics
Statistics
- Statistics Fundamentals
- Descriptive and Inferential Statistics (Measures of Central tendency, variance, deviation, frequency, symmetry, peakedness, ranking, etc…)
- Understanding data distributions (Discrete, continuous) & relationships
- Sampling & Statistical Inference
- Concept of standard error and the central limit theorem
- Concept of Confidence Intervals
- Hypothesis Testing
- Statistical Methods – Z/t-tests (One sample, independent, paired), ANOVA, Correlation, and Chi-square – Applications – Implementation in Python (scipy-stats module)
Predictive Modeling, Machine Learning & Deep Learning
Predictive Modeling & Machine Learning (Supervised & Unsupervised), Introduction to Deep Learning
- Predictive Modeling, Types of Business Problems, Getting Started with Machine Learning & Foundations of ML
- Different Phases of ML Models, Data Preparation for ML, Feature Engineering
- Concept of Supervised Learning
- Supervised Learning – Regression and Its Applications – Model Building & Validation
- Supervised Learning – Classification and Its Applications – Model Building & Validation
- ML Algorithms (Linear, Logistic Regression, Decision Trees & Ensemble Learning (Random Forest, XGboost, etc)), Tuning the parameters
- Unsupervised Learning (K-Means Clustering)
- Introduction to Deep Learning
- Introduction to Artificial Neural Networks
- Deep Learning Frameworks (Keras, Tensorflow)
- AI for ML model building
Generative AI & Nocode Agentic AI
AI Foundations
- AI vs. Automation vs. Analytics
- AI, Machine Learning (ML), Deep Learning (DL) – differences & connections
- Narrow AI vs. General AI vs. Super AI
- Core AI applications (NLP, CV, Robotics, Predictive Analytics)
Generative AI Basics
- Traditional AI vs. Gen AI
- Every day, GenAI applications
- How does GenAI work?
- Key models (GPT, Claude, Gemini, LLaMA)
- Text generation & completion techniques
- Prompt Engineering basics: role, task, context
- Core Prompting Tasks (Text generation & completion, Summarization (short & detailed), Rewriting in different tones/styles)
- Prompt Structures (instructional, role-based)
- Prompting Techniques (Zero-shot prompting, Few-shot prompting, Chain of Thought (CoT) prompting
- Role Prompting, Multi-turn interactions (context retention), etc..
- Limitations of prompting
- Evaluating GenAI output quality
Large Language Models (LLMs): How They Work
- Introduction to transformers
- LLMs vs. SLMs
- Popular LLMs (GPT, Claude, Gemini, LLaMA) – Overview – Strengths & Limitations
- Introduction to Embeddings
Introduction to Agentic AI
- No-code AI overview
- Intro to workflow automation tools
- Introduction to Zapier basics (triggers & actions), n8n workflow design, Make.com integrations
- AI-powered productivity with Notion AI for task automation & summarization, Airtable for data storage & automation, Glide for mobile app prototyping, etc.
- Design & Storytelling Tools
- Integrating AI into everyday workflows – Linking AI workflows with business processes
- Prototyping with no-code/low-code tools
What is an AI Agent? How it differs from chatbots
- Agentic AI vs. AI Agents
- Key components of Agentic AI: memory, planning, tool use, autonomy
- AI Orchestration with no-code tools
- Agent frameworks (LangChain, AutoGen, CrewAI – overview)
AI challenges: Bias, hallucination, privacy & security issues
- Responsible AI principles: Fairness, Accountability, Transparency, Explainability
- Global AI Ethics Frameworks
- Safe & Responsible usage
- Responsible AI: Guardrails
Applied Agentic AI (Agentic AI Systems using Python)
Setting up the development environment
- Installing and configuring tools like VS CODE, JUPYTER LAB, GitHub
- Best practice for managing dependencies and optimizing the workspace
- Numpy & Pandas for AI workflows
- Functions & Classes in Python
- Working with APIs (REST APIs, JSON handling, requests library)
Transformers & Fine-Tuning
- Transformers Architecture Basics(Introduction, attention, multihead attention, encoder-decoder with context)
- The Main Idea behind the Transformer
- Coding self-attention in Pytorch
- Self-attention and Masked Self-attention
- Hugging Face Transformers basics
- Pre-trained vs fine-tuned models
- Fine-tuning pre-trained models (BERT, GPT-style)
- Parameter-efficient fine-tuning (PEFT, LoRA, adapters)
GPT from Scratch
- Language modeling concepts
- Tokenization & embeddings
- Implementing a simple GPT model step by step
- Training with a toy dataset
- Training loop & loss function
Multi-Modal LLMs
- Text-to-Image models (Stable Diffusion, DALL·E)
- Image-to-text models (BLIP, CLIP, Flamingo)
- Text-to-Speech and
- Speech-to-Text APIs
- Speech-to-text (Whisper)
- Combining modalities (vision + text)
- Multi-modal pipelines (text+image, text+audio)
LLM Prompting & LangChain Basics
- LLM Wrappers & APIs
- Prompt engineering strategies
- LangChain components: Memory, Tools, Chains, Agents
- LangChain wrappers and memory
- Orchestrating LLM workflows
- Building basic agents
Vector Databases & RAG (Retrieval-Augmented Generation)
- Introduction to embeddings (SBERT, OpenAI, Cohere)
- Vector embeddings and similarity search
- FAISS & Pinecone, Weaviate for vector search
- Chunking & indexing documents
- Building RAG(Retrieval-Augmented Generation) pipelines
- Integrating Fusion & Re-ranking (Practical Sketch)
Autonomous Agents (Agentic AI)
- Introduction to LLM Agent Systems
- CrewAI & AutoGen frameworks
- Multi-agent coordination
- Task decomposition & delegation
- Building workflow-driven AI agents
- Tools, memory, reasoning
- Deployment & Use Cases
LangGraph & Model Context Protocols (MCP)
- LangGraph introduction
- Designing agent workflows with graphs
- State management in multi-agent systems
- MCP for standardized context sharing
- Future of agentic AI ecosystems
- Agent to Agent Protocols (A2A)
Testing & Evaluating LLM Apps/outputs (metrics, hallucination checks & frameworks)
- Monitoring & debugging with LangSmith
- App deployment with Streamlit, Gradio
- API deployment with FastAPI
Advanced AI (Self Paced)
Computer Vision & Reinforcement Learning
- Introduction to AI & Deep Learning (AI)
- Artificial Neural Network
- Introduction to Cloud Keras, Pytorch
- Computer Vision & Applications
- Convolution Neural Nets РArchitecture РImpl̩mentation
- Popular ImageNet models & Transfer Learning
- E2E Custom Data training framework in Pytorch
- Computer Vision – Object Detection, Encoders
- Reinforcement Learning
Data Engineering: Snowflake, Databricks, Azure Cloud (Self Paced)
Module 1: Foundations of Data Engineering
- What is Data Engineering
- ETL vs ELT concepts
- Data Warehouse vs Data Lake vs Lakehouse
- Modern Data Stack overview
- Role of Azure, Databricks, Snowflake
Module 2: Cloud Basics with Azure
- Introduction to cloud computing
- Azure core services overview
- Storage concepts (Blob, Data Lake)
- Introduction to Azure Data Factory (ADF)
- Resource setup and navigation
Module 3: Data Processing with Databricks
- Introduction to Apache Spark
- Databricks workspace overview
- PySpark basics (DataFrames, transformations)
- Data ingestion and transformation
- Writing processed data
Module 4: Data Warehousing with Snowflake
- Snowflake architecture overview
- Databases, schemas, tables
- Data loading concepts (stages, COPY)
- SQL for querying and analytics
- Compute vs storage separation
Module 5: Building Data Pipelines
- End-to-end pipeline architecture
- Data ingestion → transformation → loading
- Orchestration using Azure Data Factory
- Integrating Databricks with ADF
- Loading data into Snowflake
Module 6: Data Modeling & Optimization
- Basics of data modeling
- Fact and dimension tables
- Star vs Snowflake schema
- Query performance basics
- Partitioning and clustering concepts
Module 7: Mini Project
 (End-to-End Use Case)
*The programme also includes additional modules designed to enhance your learning experience.
Download the brochure to view the complete course curriculum and module details.
Who Should Do This Course?
This executive certification course is recommended for professionals with a minimum of 2 years of work experience. Exceptions to this requirement may be considered based on your performance and academic profile. Due to the comprehensive nature of the program, these exceptions are evaluated rigorously.
The curriculum encompasses a comprehensive suite of in-depth modules and culminates in certification along with the IIT Patna Vishlesan I-HUB Foundation and NASSCOM’s Future Skills Prime (FSP).
Job Roles & Career Progression
- Data Scientist
- Data Analyst
- Data Architect
- Business Intelligence Analyst
- Business Analyst
- GenAI Associate
- AI Analyst
- Prompt Engineer
- No-Code Automation Specialist
- AI Consultant
- AI Workflow Consultant
- GenAI Engineer
- Agentic AI Engineer
- RAG Architect
- AI Engineer
- Data Engineer
- GenAI Developer
- ML Engineer
- Workflow Automation Analyst
Capstone Projects and Assignments
The course curriculum includes various industry-relevant assignments and capstone projects that you can feature in your resume after completing.
- Business problem-related data handling, creation of dynamic dashboards, and performing ad-hoc analysis using Excel, SQL and PowerBI
- Exploratory Data Analysis - Marketing Insights for Leading E-Commerce Company
- Building a Predictive Model (Probability of Default Model) for Leading Bank using Regression
- Marketing Insights for E-Commerce Company
- Woman Clothing E-Commerce Platform- Customer Review Analysis
- Deployment of ML model and create Flask application
- RBI Circular & Banking Policy Intelligence Assistant
- AI Customer Support Agent, AI Social Media Agent
- Compliance & Policy Coach Agent
- Sales Pipeline Copilot Agent
- HR Talent & Onboarding Agent
- Loan Processing Assistant Agent (Human-in-the-Loop)
- Banking Assistant with Guardrails
- AI-powered knowledge hub with RAG + multi-agent orchestration
- Image classification, Object Detection, Finetune stable diffusion Mode
Assignments
Module 1
- Assignments & Projects
- Exercise on Basic Excel functionalities
- Problems Related to Basic Statistics
- Problems related to Mathematical foundations
Module 2
- Assignments & Projects
- Sports Analytics using Advanced Excel
- Consumer Reviews Analysis using Advanced Excel
- Retail Analytics using Power BI
- Digital Analytics using Power BI
- Retail Analytics using RDBMS-SQL
- Manufacturing Analytics using RDBMS-SQL
Module 3
- Basic Python Programming Exercises
- Data Manipulation- Visualization Exercises
- Exploratory Data Analysis – Retail Analytics
- Exploratory Data Analysis – Credit Card Analytics
- Exploratory Data Analysis – Insurance Claims Analytics
- Data Visualization Exercise for Various Business Scenarios
Module 4
- Basic Statistics – Statistical Methods Case Study
- Statistical Methods – Campaign Analytics
- Statistical Methods – Customer Experience
- Predictive Modeling – Banking
- Predictive Modeling – Automobile
- Predictive Modeling – Credit Risk
- Predictive Modeling – HR Analytics
Module 5
- Banking Case Study
- Cyber Security Case Study
- Customer Segmentation
- Customer Segmentation
- Sales Forecasting
- Demand Estimation
Module 6
- End to End Text Processing, EDA & Sentiment Analysis for Leading Hotel Chains by Analyzing Customer Reviews
- SMS Spam Filtering
- E-Commerce/Social Media Analytics
Module 7
- Fraud Classification using ANN
- Finetune any 7B params pre-trained LLM model on Databricks Dolly 15k dataset
- Scrape a webpage and RAG to create a QA interface with the content
- Image Classification
- Object Detection
- Finetune Stable Diffusion Model
Module 8
- Building Flask Applications and deploying ML models on various clouds (Heroku, GCP, Azure)
Module 9
- Integration of MS Office & Google Sheets with AI tools
- Creation of Presentation using AI Tools
- Generating HTML code & creating a simple website
- Generating e-commerce photos and promotional banners for products
Module 10
- Build Chatbots using ChatGPT API
- Build the RAG System using the Llama Index
- Developing own LLM application using Prompt Engineering
Programming Tools and Languages
Training Modes
Classroom & Bootcamp
An immersive, in-person learning experience designed to accelerate skill development through intensive, hands-on training and expert mentorship. It bridges the gap between theory and real-world application, equipping learners with the expertise and skills needed to succeed in today’s dynamic professional landscape.
Interactive Live Online
Blend classroom dynamics with engaging, real-time interactive Online sessions tailored to busy schedules. This innovative approach combines traditional and digital learning, ensuring effective knowledge retention. Experience deeper understanding through flexible, responsive instruction designed for modern learners.
Blended eLearning
Fuse the rich atmosphere of classroom instruction with the flexibility and accessibility of eLearning modules, meticulously integrated to accommodate learning preferences. This unique blend ensures an optimal learning experience, empowering participants to delve into subjects deeply.
Flexible Payment Options Across All Plans
Pay in up to 3 instalments · 0% Interest EMI via education financing partners · High-ROI programmes designed to deliver measurable career outcomes
Course Fees
Select the course you want to Enroll:
Classroom Sessions
Flexible Payment Options Across All Plans
Pay in up to 3 instalments · 0% Interest EMI via education financing partners · High-ROI programmes designed to deliver measurable career outcomes
EMI starts @ 8,260
EMI Options
*Pay in easy EMIs starting at INR ₹6387 per month.
- Fees payable in up to 3 installment​s
- 0% Interest EMI – Pay in Easy Installments (though education financing partners)
- Cost-effective courses with high ROI, making it worth every penny you invest.
Interactive Live Online
₹ 76,700/- including taxes
EMI starts @ 8,260
EMI Options
*Pay in easy EMIs starting at INR ₹6387 per month.
- Fees payable in up to 3 installment​s
- 0% Interest EMI – Pay in Easy Installments (though education financing partners)
- Cost-effective courses with high ROI, making it worth every penny you invest.
Blended eLearning
₹ 70,800/- including taxes
EMI starts @ 8,260
EMI Options
*Pay in easy EMIs starting at INR ₹6387 per month.
- Fees payable in up to 3 installment​s
- 0% Interest EMI – Pay in Easy Installments (though education financing partners)
- Cost-effective courses with high ROI, making it worth every penny you invest.
Certification
AnalytixLabs certifications are highly valued across the industry, backed by a rigorous assessment process including case studies, MCQs, and viva evaluations. Certification is awarded on successful completion of all requirements within the defined timelines. Candidates get two attempts per assessment, and certification must be completed within one year of enrolment.
You also earn credentials from our esteemed academic and industry partners:
1. TIH Knowledge Partner Certification: TIH at IIT Patna
Certification under the IIT Patna Vishlesan I-HUB Foundation knowledge partner programme. This includes virtual guest lecture sessions by TIH-associated experts, supplementary to the regular curriculum.
2. NASSCOM-FutureSkills Prime (FSP)
NASSCOM-approved certification, supported by MeitY, Government of India, and aligned to India’s Trillion Dollar Digital Economy mission, covering Analytics and Data Science.
Career Support
At AnalytixLabs, we’re committed to helping you build successful careers in AI, Data Science, and Analytics. With comprehensive placement assistance integrated into our certification programs, our dedicated team of industry professionals offers personalized support based on your educational background and work experience. The placement process is designed to equip you with both opportunity and readiness—helping you transition seamlessly into the data-driven workforce.
Accelerate your career with our Job Guarantee Program:Â https://www.
Placement Readiness Program
The Placement Readiness Program is a 6–8 week, industry-aligned module designed to give you a competitive edge after certification.
It goes beyond technical skills, offering expert guidance on resume building, interview coaching, and real-world simulations. With strong industry referrals, strategic job search planning, and personalized feedback, the program ensures you're not just prepared for the job market—you’re ready to stand out in it.
Diverse Job Opportunities
• Access to job opportunities through direct collaborations with organizations, reputed recruiters, and the extensive AnalytixLabs Alumni network.
• Many students receive multiple interview calls and see a significant boost in career prospects.
• Success, however, depends on a combination of the candidate’s dedication and the institute’s support. Active participation and timely course completion are essential for maximizing placement outcomes.
Continued Career Support
Your journey with AnalytixLabs doesn’t end after completing the Placement Readiness Program. We offer ongoing placement support to ensure you stay on track until you achieve your career goals.
Our dedicated team continues to assist with job opportunities, interview preparation, and personalized guidance as long as you need it. Many of our students benefit from multiple interview calls and long-term career growth, thanks to the strong foundation and in-demand skills built during the course.
How To Apply
select your course, complete the registration form, and make payment.
Submit your application
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Give a selection test
Take the selection test to demonstrate your skills and knowledge. This will help us assess your readiness for the course.
Reserve your seat
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Payment
Complete your payment to finalize your enrollment in the course. Choose your preferred payment method and follow the prompts to proceed.
What Students Say About Us?
True Stories, Transformative Career Experience
Piyush Ganar, Class of 2012 IIM Ahmedabad
(Director of Operations, Kenty.AI)
The course material is very easy to understand and the case studies were based on real time business problems. What I love the most about Sumeet and his team is that they never operated the institute like a typical commercial enterprise but more like a temple for learning. The gates of Alabs are always open for students for any kind of help and guidance. I would recommend ALabs to all.
Raajeev Kumar Sahu
(Senior Manager – Data Science, FinTech Startup)
I am from Advance Big Data Science course of Nov 2016 batch. The course was very structured and got real world problems to practice during the final case studies. It has also boosted my skills to start participating in the hackathons. Chandra sir was really helped me in preparing my resume right from very beginning of the course. Also, the placement team was very well organized and connected to industry leaders so that people get the right opportunity right after completing the course. I really recommend this institute, who are interested to transition into analytics field.
Sumit Asthana
(Assistant Manager, Senior Data Scientist)
The rapid pace at which the institutes are mushrooming all over India and Facebook newsfeed being inundated with thousands of options for analytics training, there are only handful of training institutes or rather say only couple of places where they prepare you to foray into rapidly growing analytics vertical. I have been working into legacy systems for past 5 years and was quite apprehensive if I will ever break into data science successfully.
Surbhi Sultania
(Analytics Manager, Mastercard Data & Services)
I took three months Big Data training from Analytix labs. Before joining this course, I had so many questions and doubts that will this course be worthy enough but later I found myself lucky to join this program. All trainers are amazing and always ready to help. Live examples and Case Studies are given which helps in understanding the concept and hands on practice.Not only they help in quality in depth knowledge transfer but also tend to give right direction to your career.
Vibhu Gautam
(Professor of Practice – Computer Science, UPES)
I had been associated with AnalytixLabs since 2012. This has been possible because of the mentor ship and support you get from faculty there specially from Sumeet and Chandra.I did a Business Analytic course with a focus on Marketing Analytic. The course deliver had been great and most importantly you never feel like you are part of formal classroom teaching. You are mentored there at every step, from Code Errors to Understanding Statistics behind it.Â
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- Get access to trial sessions to choose the most suitable course.
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Frequently Asked Questions
Does an artificial intelligence course require coding?
Absolutely, coding skills are often a prerequisite for artificial intelligence (AI) courses. Nonetheless, our best artificial intelligence online course is uniquely designed to accommodate individuals without coding experience.
Whether you’re new to programming or have a limited technical background, our online courses for AI start from the fundamentals. You’ll learn AI concepts step by step, build a solid foundation, and acquire essential artificial intelligence and machine learning skills.
Through our comprehensive approach, you’ll gain confidence and proficiency in applying AI techniques to real-world challenges, empowering you to succeed in this rapidly evolving domain.
Do you provide guaranteed placement?
Our placement assistance programs vary by course.
For Nasscom-FutureSkills Prime Certified Courses: We offer a Job Guarantee with 50% Fee Refund and Minimum Package Assurance. If you’re unable to secure a qualifying position with the assured minimum annual package within 6 months of certification (after fulfilling the stipulated requirements), we will refund 50% of your course fee.
For other courses: While they do not carry a placement guarantee, they include a dedicated 2-month industry-focused placement readiness module. This covers technical and soft skills training, interview preparation through topic recaps, practice tests, case studies, simulated recruitment drives, and mock interviews with industry experts—ensuring you are well-prepared and confident to secure the right opportunities.
What is the difference between artificial intelligence and machine learning?
Artificial intelligence (AI) and machine learning (ML) are closely intertwined concepts with distinct technological meanings and applications.
Artificial intelligence encompasses machines intelligently performing tasks, resembling various human cognitive functions like learning, problem-solving, and perception. It aims to develop systems that exhibit behaviors typically associated with human intelligence.
On the contrary, machine learning is a specialized area within artificial intelligence that focuses on developing algorithms that can help computers learn from data and make predictions or decisions autonomously.
ML algorithms leverage statistical techniques to improve their performance on specific tasks over time, learning from patterns in the data without explicit programming instructions.
AI is designed to build intelligent machines capable of simulating human behavior.
ML is a specific technique or approach within AI that involves developing algorithms to enable machines to learn from data and make decisions or predictions.
What academic background is essential to enroll in this artificial intelligence and machine learning course?
Individuals from various technical or quantitative disciplines, such as engineering, mathematics, statistics, and business management, aspire to strengthen their proficiency in advanced analytics, AI, and machine learning. After completing the Machine Learning and AI courses, they excel at leveraging these technologies for advanced applications.
A robust technical foundation and a genuine passion for artificial intelligence will give you a notable edge as you launch your career path after completing our comprehensive applied AI courses.
What jobs can I get after completing this AI and ML course?
Upon completing this course, your skills will be highly receptive to the job market. An array of exciting opportunities and diverse roles await exploration, including positions such as:
- AI ML Specialist
- AI Specialist
- Analytics Consultant
- Data Science Specialist
- Data Science Consultant
- Data Scientist
- Machine Learning Specialist
- Statistical Analyst
These roles represent a glimpse into the many career paths in artificial intelligence, machine learning, analytics, and data science. Each role offers unique challenges and growth prospects tailored to individuals with a strong foundation in these areas.
Is this a full online AI course training session or a classroom?
AnalytixLabs offers three distinct delivery formats for artificial intelligence courses online, meticulously tailored to accommodate the diverse needs of our valued clientele. We offer both online and classroom training sessions for our students and classroom blended E-Learning slots.
How will I know if this course is right for me?
Choosing the right course for your career is a significant decision. It involves carefully examining curriculum, duration, projects, and more.
Suppose you come from a technical or quantitative background with a degree or experience in Engineering, Mathematics, Statistics, or Business Management, and you’re eager to excel in AI and machine learning. In that case, our course is tailor-made for you. We’ve outlined all the course specifics above.
In our AI and ML courses, you’ll benefit from learning from industry-leading experts with substantial field experience. Our course fee is set according to industry standards. For further information, feel free to explore our brochure for comprehensive details.
When will I have access to learning materials if I enroll?
Access to LMS and course materials is granted for a period of one year. Additionally, you can retake any classes as needed within the subsequent year following course completion, subject to batch change policies.
Please note that for AnalytixLabs content, the typical access duration to co-branded global certification materials is limited to six months.
For genuine circumstances requiring further access to our artificial intelligence courses, recording access can be extended up to one year after the initial one-year validity period. It’s important to recognize that our courses are continuously updated to reflect industry developments, and older content may become outdated. Therefore, we do not guarantee lifetime access merely for promotional purposes.
Is there a free version of this course?
While we don’t currently provide an artificial intelligence free course, we actively engage with learners through informative and interactive webinars. These webinars focus on the latest developments and technologies in the industry, offering valuable insights that you can leverage to enhance your understanding of AI. We encourage you to join these sessions to stay updated and informed.
In addition to our webinars, you can explore a wealth of knowledge on AI-related topics through our AnalytixLabs Blogs and Medium Channel channels. These resources are designed to broaden your horizons and deepen your expertise in the domain, covering various subjects, from basic concepts to advanced applications.
Is this course for graduates or experienced professionals?
Our expansive and dynamic artificial intelligence courses offered online are thoughtfully designed to accommodate a wide range of learners, including college students, recent graduates, and professionals currently active in their careers.
This comprehensive course is particularly well-suited for individuals with a strong technical or quantitative foundation, such as those with backgrounds in Engineering, Mathematics, Statistics, Business Management, or related fields.
Whether you want to deepen your knowledge, transition to a new career path, or enhance your current skill set, our program provides the ideal opportunity to thrive in the exciting field of artificial intelligence.
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