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Data Analytics Certification Course Overview

The Data Analytics & AI Certification Course is a 10-week live online program designed for aspiring analysts who want to stay ahead. You can also be ready for IIBA CBDA Certification.

You’ll master core data analytics tools like SQL and Power BI, and learn how to leverage AI tools like AutoML, Generative AI, and No-Code AI platforms to solve real business problems.

Through hands-on projects, you’ll graduate with the skills to not just analyze data—but drive intelligent decisions with AI.

Key Features of Our Data Analytics & AI Certification Course

Learn about the key features of our Data Analytics & AI Certification Training program in this section.

AI-Integrated Curriculum

Learn how AI enhances data preparation, analysis, and reporting using AutoML, Generative AI, and NLP tools.

Hands-On Projects with
Business Use Cases

Apply both analytics and AI concepts through real-world case studies and a Capstone Project: Build an Intelligent Business App.

Master Tools Like SQL, Power
BI & No-Code AI Platforms

Work with essential analytics tools and AI builders like Power BI, Microsoft Power Apps, and OpenAI APIs.

Generative AI for Analysts

Automate SQL writing, create executive summaries, and debug code using tools like ChatGPT and DeepSeek.

Live Online Classes +
Mentorship

Get guidance from expert trainers to help you succeed in mastering Data Analytics & AI

Career Support & Certification

Receive a verifiable certificate, resume reviews, and mock interviews to prepare for AI-era data analytics roles.



Who Should Enroll in Data Analytics Certification Courses?

logo Aspiring Data Analysts & Business Analysts
logo Professionals from non-tech backgrounds looking to break into analytics
logo Business professionals seeking to upskill with AI + Data skills
logo Students and freshers with strong interest in analytics and AI
logo Teams undergoing upskilling in corporate environments

Do I need to learn programming?

logo No, if you don’t like or are not good at programming, this course is designed for you.
logo This course will not require you to learn programming skills in depth, minimal exposure to programming is required.

Skills Covered

logo Data Analytics Fundamentals
logo Descriptive Analytics
logo Diagnostic Analytics
logo Predictive Analytics
logo Prescriptive Analytics
logo Machine Learning
logo SQL for Data Extraction
logo Power BI for Business Dashboards
logo AI-Powered Data Preparation
logo Intelligent EDA & Auto Insights
logo AutoML Platforms
logo Model Interpretation
logo Generative AI for Analysts
logo Trend Analysis
logo AI App Development

View More...


The Value of Data Analytics Certification Courses: Are They Worth It?


Data Analytics Market


One of the fastest growing segments

The global data and analytics market size is expected to be US$ 184.53 billion by 2027, growing at 12.85% (CAGR)

Source: GlobalData

Top Employers


All the top MNCs need Data Analytics professionls

Data-Analytics-sector-outlook

Source : www.reportsanddata.com

Accenture SP-Global Labcorp capgemini
TCS Capital-One USSA Northrop-Grumman Bloomberg
capgemini Northrop-Grumman Bloomberg


Course Testimonials

Elzahn Oosthuizen

Elzahn Oosthuizen

CBDA Certified

Senior Specialist: Business Analyst at Altron Systems Integration
City of Cape Town, South Africa



The TechCanvass IIBA-CBDA online course is really comprehensive and well structured. ...Read More
The mind maps and cheat sheets also really helped providing good summary material. The mock questions and 4 full test exams also really helped me to prepare properly for the exams. The course material and mock exams are of a very high standard and also summarized nicely everything that is important for the exam. Passed with higher for most domains on my first attempt thanks to TechCanvass! I also liked the fact that TechCanvass contacted me directly and checked in on my progress as well as inform me that I can ask for additional assistance whenever required. Read Less



Kelly Byers

A.N.M. Shibly

CBDA Certified

Chief Operating Officer at Avis Technologies Limited
Bangladesh



The course videos, activities were excellent. But the best part, for me, was the mock tests. These tests helped me a lot to ...Read More
identify my weak areas, and also gave me a thought process to study. When I decided to participate in the certification exam of Certified Business Data Analytics (CBDA), I searched through Internet for training courses. There I met Techcanvass. Apart from the book of CBDA, all the contents for this test, I got from Techcanvass. Thanks to Techcanvass for being with me in journey." Read Less



Soham K

Soham K

CBDA Certified

Data analytics Consultant at Integrated Learning Systems(ILS)
India



The CBDA self-learning course helped in providing video lectures, innovative learning techniques like mind maps and ...Read More
puzzle games. A section of Mock tests provide a real time experience of examination with a good difficulty level to train you for the actual exam. The CBDA self-learning course has case studies which provide an idea of approaching business problems and using visualizations for analysis. Apart from this, I had read the official guide to business data analytics and had previous experience of data analyst to my advantage. I would like to thank Techcanvass for providing essential material to achieve this certification. Read Less




View more Reviews


Course Curriculum

Trainer and Mentor


Vinayak-M-Kesari Vinayak-M-Kesari
Mr. Vinayak M Kesari
Sr. Data Analyst

Currently working as Senior Data Analyst with over 17 years of experience, specializing in diverse domains such as ERP, Payment, Banking and Retail. Have achieved prestigious IIBA CBDA (Certification in Business Data Analytics) certification and have acquired ML certification from IBM. ...Read More
Has expertise in leveraging data for strategic insights, software product management, and driving informed decision-making in dynamic business environments. Read Less



Data Analytics Certification Courses: Syllabus Details

The training program will cover all the topics as mentioned below:

Course Project: Learners will be required to do a complete project in a group setup working on every phase of the Data Analytics lifecycle. This will help you in applying the skills and techniques, acquired during the sessions.


Course Overview
1 Course Learning Objectives
2 Syllabus
3 Data Analytics Certification (CBDA)
4 Take-aways
Introduction to Data Analytics
1 What is Data Analytics?
2 Importance of Data Analytics
3 Key Elements of Data Analytics
4 Opportunities and Careers paths in Data Analytics
5 Roles and responsibilities of a Data Analyst
Types of Data Analytics
1 Descriptive Data Analytics
2 Predictive Data Analytics
3 Diagnostic Data Analytics
4 Prescriptive Data Analytics
5 Quiz
SQL for Sourcing Data
  • SQL Overview
  • Data Query Language
  • Data Manipulation Language
  • Accessing Data from Multiple Tables
2 Class Exercises
Data Visualization with Power BI
  • Fundamentals of Data Visualization
  • Introduction to Power BI
  • Data Visualization using Power BI
  • Slicers and Filters in Power BI
  • Interactive Visualisations in Power BI
  • Creating Paginated Report
  • Creating Dashboards in Power BI
Phase I - Identify the Research Questions
  • Define Business Problem or Opportunity.
  • Identify and Understand the Stakeholders,
  • Assess Current State,
  • Define Future State,
  • Formulate Research Questions,
  • Plan Business Data Analytics Approach, and
  • Select Techniques for Identify the Research Questions
Phase II - Source Data
  • Plan Data Collection,
  • Determine the Data Sets,
  • Collect Data, and
  • Validate Data.
Phase III - Analyze Data (Cleaning, Transformation and Analyzing data)
  • Develop Data Analysis Plan,
  • Prepare Data,
  • Explore Data,
  • Perform Data Analysis, and
  • Assess the Analytics and System Approach Taken
Phase IV - Interpret and Report Results
  • Validate Understanding of Stakeholders,
  • Plan Stakeholder Communication,
  • Determine Communication Needs of Stakeholders,
  • Derive Insights from Data, and
  • Document and Communicate Findings from Completed Analysis, and
  • Select Techniques for Interpret and Reporting Results
Phase V - Use Results to Influence Business Decision-Making
  • Recommend Actions,
  • Develop Implementation Plan, and
  • Manage Change.
Phase VI - Guide Organizational-Level Strategy for Business Data Analytics
  • Organizational Strategy,
  • Talent Strategy, and
  • Data Strategy.
LLM
  • LLM Models
  • Tokenization
  • Fine Tuning
  • GAN
  • RAG
Machine Learning Basics
  • What is Machine Learning
    • NLP
    • Neural Network
  • Supervised Learning
    • Linear (Continuous) Regression
    • Categorical Classification
  • Unsupervised Learning
    • Recommendations
    • Clustering
    • Dimensional Reduction
Artificial Intelligence and Generative AI Fundamentals
  • What are AI and Generative AI
  • How does it work?
  • How can you use for better efficiency
  • More use cases
Leveraging AI for Enhanced Data Analytics
  • AI-Powered Data Preparation & Augmentation
  • Intelligent Exploratory Data Analysis (EDA)
  • Applied Predictive Analytics
  • Generative AI for the Data Analyst
Learning to Develop Practical AI Applications
  • Building with AI APIs
  • Low-Code/No-Code AI App Development

Class and Course Projects


Intelligent-App

The "Intelligent App" Challenge

Analyzes historical sales data and displays key trends in a Power BI dashboard (Part 1 skill).

Integrates an AutoML model to predict future sales for a given product (Part 1 skill).

Includes a feature using an LLM API to provide a plain-language summary of the forecast (Part 2 skill).


CBDA Course Syllabus

Fundamentals of Data Science/Analytics
1 Introduction to Data Science/Analytics
2 Use cases for Data Science/Analytics
3 Data Science lifecycle
4 Types of Data Analytics.
5 Artificial Intelligence/Machine Learning overview
Introduction to Certification in Business data analytics (CBDA)
1 Eligibility Criteria
2 Six Business Data Analytics Domains
Business Analysis and Data Analytics
1 Business Analysis in Data Analytics Projects
2 Business Analysis Vs Data Analytics
Introduction to Business Data analytics Domains
1 Identify the Research Questions – 20% (Domain 1)
2 Source Data – 15% (Domain 2)
3 Analyze Data – 16% (Domain 3)
4 Interpret and Report Results – 20% (Domain 4)
5 Use Results to Influence Business Decision Making – 20% (Domain 5)
6 Guide Organization-level Strategy for Business Analytics - 9% (Domain 6)
Domain 1: Identify the Research Questions
1 Define Business Problem or Opportunity.
2 Identify and Understand the Stakeholders,
3 Assess Current State,
4 Define Future State,
5 Formulate Research Questions,
6 Plan Business Data Analytics Approach, and
7 Select Techniques for Identify the Research Questions
Domain 2: Source Data
1 Plan Data Collection,
2 Determine the Data Sets,
3 Collect Data, and
4 Validate Data.
Domain 3: Analyze Data
1 Develop Data Analysis Plan,
2 Prepare Data,
3 Explore Data,
4 Perform Data Analysis, and
5 Assess the Analytics and System Approach Taken
Domain 4: Interpret and Report Results
1 Validate Understanding of Stakeholders,
2 Plan Stakeholder Communication,
3 Determine Communication Needs of Stakeholders,
4 Derive Insights from Data, and
5 Document and Communicate Findings from Completed Analysis, and
6 Select Techniques for Interpret and Reporting Results
Domain 5: Use Results to Influence Business Decision-Making
1 Recommend Actions,
2 Develop Implementation Plan, and
3 Manage Change.
Domain 6: Guide Organizational-Level Strategy for Business Data Analytics
1 Organizational Strategy,
2 Talent Strategy, and
3 Data Strategy.
Techniques
1 Business Simulation
2 Business Visualizations
3 Concept Modelling
4 Data Dictionary
5 Data Flow Diagrams
6 Data Mapping
7 Data Storytelling
8 Decision Modelling and Analysis
9 Descriptive and Inferential Statistics
10 Extract, Transform, and Load (ETL)
11 Exploratory Data Analysis
12 Hypothesis Formulation and Testing
13 Interface Analysis
14 Optimization
15 Problem Shaping and Reframing
16 Stakeholder List, Map, or Personas
17 Survey and Questionnaire
18 Technical Visualizations
19 The Big Idea
20 3-Minute Story
Case Studies
1 Domain 1: Fraud Detection and Predictive Analytics Case study at an Investment bank
2 Domain 2: Voice termination fraud Case study
3 Domain 3: Exploratory Data analysis and Life Insurance company Case study
4 Domain 4: HiFive Ice cream Case Study
5 Domain 5: E-commerce retailer and UK giftware and online gifting industry
6 Domain 6: E-commerce retailer Case study



Course Certificate


Every course participant will receive a course completion certification from Techcanvass as shown on the right.

Data-Analytics-Certification-Training


Data Analytics Fees


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Data Analytics and AI Training

[10% Early Bird Discount Available]

₹ 34,900

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Expires in 01 D 11 H 09 M 25 S



  • Live Online Training (10 weeks)
  • No pre-requisites
  • Unlimited Portal Access
  • Includes real-life project
  • Access to Experts through multiple modes
  • Proficiency Certificate
  • Recorded Sessions available

To get Group Discount Click Here



Data Analytics and AI Training with CBDA Certification

[10% Early Bird Discount Available]

₹ 39,000

[GST Extra]

Expires in 01 D 11 H 09 M 25 S



Advance your career with a powerful blend of Data Analytics, AI, and CBDA.

Course Overview

Study Materials & Case
Studies

CBDA Question Bank

Advance Module


To get More Details, Click Here




Have questions? Call the learning advisor or join the Whatsapp community for career Q&A, expert guidance and more

    +91 93255 66777
    Join the Whatsapp Group


Upcoming Batches


Data Analytics Online Training Schedule

Time Zone :


Batch starts Batch Timing Early bird discount 10% Offer Code Expires in
Batch Start Date and Time Early Bird Discount and Validity
02 August 2025 02 August 2025

Sat - Sunday

07:30 AM - 10:30 AM (IST)

Sat - Sunday

07:30 AM - 10:30 AM (IST)
10% off  (Valid Till 12th Jul)
Use code DTAN2313
12 July 2025 23:59:59
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Sat - Sunday

07:30 AM - 10:30 AM (IST)

Sat - Sunday

07:30 AM - 10:30 AM (IST)
10% off  (Valid Till 21st Sept)
Use code DTAN2314
21 September 2025 23:59:59
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Use code DTAN2314
 21 September 2025 23:59:59
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Sat - Sunday

07:30 AM - 10:30 AM (IST)

Sat - Sunday

07:30 AM - 10:30 AM (IST)
10% off  (Valid Till 30th Oct)
Use code DTAN2323
30 October 2025 23:59:59
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 30 October 2025 23:59:59

You can attend the classes from any part of the world, check your country here:    

Corporate and Group Training

Let us know about your company training requirements, we can also customize the program to suit your needs.

Special discounts available for a group of 3 or more.

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Data Analytics Training FAQs


Is business analytics or Data Analytics certificate worth it?
A certification in Data Analytics field demonstrates your ability and the commitment for the field. It also shows the employers that you have the ability to analyse data through complex data analytics methods, help the customer make strategic decisions, and develop sustainable business growth
Which certification is the best for business analytics?
There are several business analytics certifications. Some of the top ones are as follows:
  • IIBA Certification in Business Data Analytics (CBDA) – Our course includes this certification preparation.
  • Coursera Data Analytics Certification
  • Google Data Analytics Certification
  • IBM Data Analytics Certification
Should I do business analytics course or an MBA?

There are couple of ways you can master Data Analytics skills – Long term masters program (12 months to 18 months) or short term certificate course like this one.

It depends on your current background. Long term programs are better suited for freshers (any graduate) or professionals with 1-2 years’ experience in programming or tech roles.

Short term certification courses are designed for experienced professionals, specially with non-programming background. If you are a Business Analyst, Project Lead or a Manager or a testing professional, you can go for the short-term courses.

How long does it take to get a data analytics certification course?
Our Data Analytics online training course is 6 weeks long. All the short term courses vary from 6 weeks to 9 weeks. Though MBA or PG program in Analytics are of 12-18 months duration.
Is data analyst easier than coding?
Data Analysis is a very broad term. One can make a career in Data Analysis as a tech person with programming skills or without programming skills. For example, a reporting analysis and data visualization professionals don’t need much of programming skills. But roles like Data Engineers and Data scientists are completely technical role and need good programming skills.
What course should I do for data analyst?
We have provided an answer to this question in this FAQ section - Should I do business analytics course or an MBA?
What is the best way to learn data analytics?

Data Analytics is a vast field, so start by assessing your aptitude. Whether you're from a programming or non-programming background, a Data Analytics Certification Course helps you choose the right path.

Would you like to talk to our experts. Drop us an email at info@techcanvass.com with your background.

Which company hires most data scientist in India?

Generally, most of the top IT companies are doing projects in Data Analytics. Some of the top employers are:

  • Accenture Analytics.
  • Mu Sigma.
  • Swiggy.
  • Amazon.
  • Tiger Analytics.
  • Oracle.
  • Latent View.
  • Microsoft.
Do I need to have a programming background to enter the Data Analytics field?
No, you don’t necessarily need a programming background to enter the Data Analytics field. However, having some knowledge of programming languages like Python or R can be beneficial in handling and analyzing large datasets. It’s important to note that many data analytics tools and platforms provide user-friendly interfaces that require minimal coding. So, while programming can enhance your data analytics skills, it’s not a strict prerequisite.
How does Data Analytics skill boost my career?
Data Analytics skills can significantly boost your career as these skills are in high demand across various industries. These skills can help you make informed decisions, predict trends, and improve business strategies. This inturn can make you a valuable asset to any organization, opening up opportunities for promotions and higher compensation. Additionally, the demand for data analytics skills spans across various industries, providing a wide range of career options.
What is Data Analytics?
Data Analytics is the process of examining, cleaning, transforming, and modeling data with the goal of discovering useful information, drawing conclusions, and supporting decision-making. It involves a range of techniques and methodologies to analyze data from various sources in different formats, both structured and unstructured. Data Analytics allows us to make sense of vast amounts of data to help businesses and organizations make better decisions and predictions.
What are the differences between Data Science and Data Analytics?
Data Science and Data Analytics are two distinct fields, though they overlap in many areas.
Data Science is a broader field that includes various techniques such as machine learning, predictive modeling, and statistics. It involves extracting insights from various forms of data, both structured and unstructured. Data Science is more focused on designing and constructing new processes for data modeling and production using prototypes, algorithms, predictive models, and custom analysis.
On the other hand, Data Analytics is more focused on processing and performing statistical analysis on existing datasets. It is used to discover useful information and aid in business decision making. Data Analytics tends to be more business and process-oriented.
In summary, while both fields involve working with data, the main difference lies in the scope and focus of what they do with this data.
What are the salaries of a Data Analytics professional in India and US?
The salaries of a Data Analytics professional can vary widely depending on the industry, location, and level of expertise.
In India, the average salary for a Data Analyst is around ₹6,72,500 per year. If a person has experience of 2-3 years then the figure may increase up to ₹6-8 LPA. However, the salary can go up to as much as INR 22 LPA.
In the United States, the average salary for a Data Analyst is around $67,063 per year. However, the salary can range from $49,000 to $92,000 per year, and can even go up to $120,591 per year depending on the level of expertise and the state they are working in.
Please note that these figures are averages and actual salaries can vary. It’s also important to note that salaries are often accompanied by other forms of compensation such as bonuses, profit sharing, and benefits.
SOURCE: Payscale.com and Indeed.com
What is the career path of a Data Analytics professional?
The career path of a Data Analytics professional can vary based on individual goals and interests, but a typical path might look like this:
  • Entry-Level Positions: After obtaining a relevant degree, one might start as a Data Analyst or Junior Data Analyst, where the primary tasks involve processing and making sense of large datasets.
  • Mid-Level Positions: With a few years of experience, one could move into roles such as Senior Data Analyst, Data Scientist, or Data Engineer, where the tasks might involve more complex data analysis, predictive modeling, and machine learning.
  • Management and Beyond: After gaining substantial experience and expertise, one could aim for leadership roles such as Data Analytics Manager, Director of Data Science, or even Chief Data Officer. These roles involve overseeing data strategies and policies in an organization.
How does this "Data Analytics and AI course" differ from a traditional data analytics course?
This course goes beyond traditional data analytics by integrating cutting-edge AI techniques. You'll learn not just to analyze historical data, but also to leverage AI for automated data preparation, intelligent insights, predictive modeling using AutoML, and even building practical AI applications, setting you apart in the job market.
What specific AI tools and technologies will I learn in this course?
Our Data Analytics and AI course covers practical AI tools and libraries such as PyOD, KNN Imputation, Recordlinkage, featuretools, SMOTE for data preparation; Sweetviz for intelligent EDA; Microsoft Azure AutoML for predictive analytics; and how to build applications using leading AI APIs (OpenAI, Gemini via Python) and low-code platforms like n8n or Power Apps.
Do I need a strong coding background for the AI modules in this course?
No, this Data Analytics and AI course is designed for beginners. While there's minimal exposure to Python for practical application of AI libraries, the focus is on using AI tools and platforms (like AutoML, AI APIs, and low-code solutions) rather than deep programming or complex algorithm development. We emphasize practical application over theoretical programming.
How will learning AI in this course boost my career as a Data Analyst?
Adding AI skills to your data analytics expertise makes you a 'future-proof' analyst. You'll be able to automate tedious tasks, extract deeper and faster insights, build more accurate predictive models, and even develop intelligent applications, making you highly valuable to employers looking for advanced, efficient data professionals.
What kind of AI applications will I be able to build after completing this course?
You will gain the skills to build practical AI applications like sentiment analyzers for customer reviews, text summarizers, marketing copy generators, sales forecasting apps, and even image recognition tools, often by leveraging powerful AI APIs and low-code platforms.


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