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Certificate in Data Analytics with AI Foundation
In an era where decisions are driven by data, the ability to analyze, interpret, and apply information has become an indispensable professional skill across industries. The Certificate in Data Analytics with AI foundation + IBM module program by Win In Life Academy is designed to build your analytical foundation and practical competence through structured learning and guided application. Over four months, you will gain proficiency in essential tools and methodologies for data collection, cleaning, exploration, modeling, and visualization, enabling you to transform data into meaningful insights. This program is ideal for aspiring professionals and learners seeking to strengthen their analytical capabilities or transition into data-focused roles. It emphasizes conceptual clarity, technical precision, and real-world applicability to empower you to make informed, evidence-based decisions. Develop a data mindset. Decode patterns. Drive smarter outcomes.
Program Details
4
Months
Key Takeaways of Data Analytics Course
- Actionable Insights : Master the entire data lifecycle; from raw data source to insight generation. Learn to structure, clean, and validate chaotic datasets using statistical methods and AI-assisted tools, ensuring every decision you make is data-driven and impactful.
- Tools and Technique : Gain hands-on proficiency in Excel, SQL, Python (Pandas, NumPy, Matplotlib), Power BI, and Tableau. Work with ETL pipelines, AutoML frameworks, and AI-powered analytics tools to visualize, model, and automate insights as a professional analyst.
- Problem-Solving Mindset : Develop analytical reasoning to ask the right business questions, evaluate data reliability, and transform findings into actionable intelligence. Strengthen your storytelling through dashboards, visual analytics, and evidence-based communication.
- Career Acceleration : Build a robust project portfolio integrating analytics and AI foundations. Prepare for high-growth roles such as Data Analyst, Business Intelligence Analyst, or AI-Enabled Reporting Specialist, supported by IBM-powered certification and career readiness modules.
Learning Summaries for Data Analytics Certification Course
- Get a comprehensive understanding of data, its types, and data analytics lifecycle. You will be able to learn how to approach a data problem from its initial stage of data collection and cleaning to data modeling, and how to communicate valuable insights.
- Gain practical expertise in using tools such as Python libraries (Pandas, NumPy, Matplotlib), and SQL for data manipulation, analysis, and Visualization. Cover the fundamental statistical concepts and their applications.
- Learn to create compelling data visualization using tools such as Tableau/Power BI and translate analytical results into actionable recommendations for organizations and stakeholders for impactful business ventures.
- Apply analytical techniques to solve practical business challenges to reinforce the ability to identify opportunities, predict data trends, and optimize business processes to improve decision-making abilities.
- Data pre-processing is Crucial: Understanding how to clean, transform, and prepare raw data (handling mission values, outliers, scaling, encoding) is fundamental for building effective machine learning models. The quality of data directly impacts model performance.
- Machine Learning Algorithms: Various algorithms (e.g., linear regression, decision trees, clustering) are suited for different types of problems (regression, classification, unsupervised learning). Choose the right algorithm that depends on the data characteristics and the desired outcomes.
- Essential Model Evaluation: Evaluate the performance of machine learning models using appropriate metrics (e.g., accuracy, precision, recall, F1-score, RMSE) and techniques (e.g., train-test split, cross-validation) to ensure generalization to unseen data.
- Bias and Variance Trade-off: Understanding the concepts (under-fitting) and variance (overfitting) and how to manage this trade-off is key to building models that perform well on new, unseen data.
- AI comes with a Range of Capabilities: Artificial Intelligence is a wider field than just machine learning, including areas like natural language processing (NLP), computer vision, and robotics, all aiming to create intelligent agents.
- Machine Learning is a Subset of AI: ML provides algorithms that enable computers to learn from data without explicit programming, forming a core component of many modern AI systems.
- Deep Learning Leverages Neural Networks: Deep learning, a subfield of ML, utilizes artificial neural networks with multiple layers to learn intricate patterns from large datasets, achieving significant breakthroughs in areas like image recognition and NLP.
- Ethical Considerations: Paramount in AI development, recognizing and addressing potential biases, fairness issues, and the societal impact of AI technologies is crucial for responsible innovation and deployment.
- Transforms Raw Data into Actionable Insights: The process involves collecting, cleaning, analysing, interpreting, and visualizing data to uncover patterns, trends, and valuable information for decision-making.
- Different Analytics Serve Different Purposes: Descriptive analytics (what happened?), diagnostic analytics (why did it happen?), predictive analytics (what will happen?), and prescriptive analytics (how can we make it happen?) provide a framework for understanding data at various levels.
- Visualization offers Effective Communication: Presenting data insights through charts, graphs, and dashboards makes complex information accessible and understandable to stakeholders, facilitating better decision-making.
- Statistical Methods Underpin Data Analysis: Understanding fundamental statistical concepts like probability, distributions, hypothesis testing, and regression analysis is essential for drawing meaningful and reliable conclusions from data.
Data Analytics AI Machine Learning
Enrolling in data analytics AI machine learning combo course offers numerous advantages in recent data-driven world. This interdisciplinary skillset is highly sought after across various industries, leading to a wide range of well-paying job roles such as Data Scientists, Machine Learning Engineer, AI Specialist, Business Intelligence Analyst, and more.
- Versatile and Future-Proof Skillset: The AI ML Data Analytics combo course provides a strong foundation in data handling, analytical techniques, and intelligent system development, making graduates adaptable to technologies and various industry needs.
- Comprehensive Understanding and Synergy: This combo course allows you for a deeper understanding of how they interrelate. The combination provides the foundation for data-driven insights, predictive modelling and automation, and boarder goal of creating intelligent systems.
- Problem-solving and Innovation Capabilities: The course equips you with the skills to analyze complex datasets, identify patterns, build intelligent solutions, and communicate data-driven insights effectively. This fosters critical thinking and collaborative opportunities to innovation.
I'm Interested in this program?
Certifications for Data Analytics with AI Foundation Course
Once you complete the dataOnce you complete the certification in data analytics with AI foundation course, you will obtain a globally recognized certificate from Win in Life Academy.
Globally Recognised Certification
Educational Board of Vocational Training and Research
Note: Let’s secure your certification for the data analytics course that you need for your career progression with training at Win in Life Academy.
Tools to be Covered in Data Analytics Course
Microsoft Excel
SQL
Python
Jupyter Notebooks
Pandas
tableau
Power BI
NumPy
- Disclaimer: The datasets, platforms, software, and tools presented within the data analytics course are specifically provided for educational purposes. It facilitates learning and understanding relevant concepts and techniques. These tools and software should not be considered suitable or optimized for production in the real-world environment.
- The given tools may have functional limits, or it may be a trial version or need specific configurations. It is for educational uses and involves inherent risks like data loss or system instability. For this, Win in Life Academy holds no guarantees or warranties regarding their accuracy, performance, reliability, or suitability beyond their educational experience.
Master 20+ essential industry tools
Data Analyst Certification Program Curriculum
Learn from the industry-led expert designed data analytics certification course for students and professionals. .
Gain a competitive edge with our comprehensive Data Analytics program, meticulously designed by industry experts to bridge academic knowledge with real-world applications. .
Pre Data Analytics Course Curriculum
Modules
Non-Technical
Module 1
English Communication & Grammar
- Basics of Communication
- Grammar and Vocabulary
- Verbal Communication Skills
- Written Communication
- Non-verbal Communication
- Confidence and Public Speaking
- Professional Communication Etiquette
- Practical Application
- Continuous Learning
Module 2
Mock Interviews
(Practice Assessment Test)
- Personal Introduction
- Technical Skills
- Problem-Solving
- Behavioral Insights
- Industry Knowledge
- Hypothetical Scenarios
- Soft Skills
Module 3
Corporate Etiquette
- Making the Most of Meetings
- Dressing Right for the Workplace
- Being Respectful and Thoughtful at Work
- Keeping Your Workspace Clean and Organized
- Using Technology Responsibly
- Dining with Manners in Professional Settings
- Building Relationships Through Networking
- Best Practices for Virtual Meetings and Online
- Communication
- Managing Your Time and Meeting Deadlines
- Understanding and Respecting Cultural Differences
- Leaving a Job Gracefully
Module 4
Aptitude
Technical Program Modules for Certificate in Data Analytics
Designed by industry professionals, this Data Analytics course offers a comprehensive, career-focused learning journey. It takes you from mastering foundational spreadsheet techniques to advanced data visualization, statistical analysis, and AI integration will equip you with practical tools, modern methodologies, and industry-ready skills for a successful career in the data-driven world.
Foundations of Data & Analytics
Module 1:
Excel & Data Analytics Foundations
- Key Tools: Excel (Formulas, Pivot Tables), AI-integrated Excel Tools
- Learning Outcomes: Build proficiency in Excel for data analytics; perform data summarization and visualization using pivot tables; understand analytics lifecycle and data types.
Highlights
Module 2:
Statistics & Data Fundamentals
- Key Tools: Descriptive Statistics, Distributions, Advanced Excel Dashboards
- Learning Outcomes: Apply statistical measures for analysis; design interactive dashboards; understand data distribution and variability.
Highlights
Module 3:
SQL Basics & Data Handling
- Key Tools: MySQL / PostgreSQL, Data Validation Tools
- Learning Outcomes: Write SQL queries (SELECT, JOIN, subqueries); clean and validate datasets; automate data correction using AI-assisted tools.
Highlights
Module 4 :
Advanced SQL & Data Auditing
- Key Tools: Window Functions, CTEs, Sampling Methods
- Learning Outcomes: Perform advanced queries; ensure data quality and reliability through auditing and sampling techniques.
Highlights
Module 5 :
Python Programming & Data Wrangling
- Key Tools: Python, Jupyter Notebook, VS Code
- Learning Outcomes: Learn Python syntax, control flow, and data structures; merge and clean datasets for analysis.
Highlights
Module 6 :
Python Analytics & Visualization
- Key Tools: NumPy, Matplotlib, Seaborn, AI-generated Visual Tools
- Learning Outcomes: Conduct numerical computation and create professional-level static and AI-assisted visualizations.
Highlights
Module 7 :
Applied Analytics Mini Project
- Key Tools: Pandas, Matplotlib, Excel
- Learning Outcomes: Execute a small project analyzing real-world datasets; present findings through peer-reviewed sessions.
Highlights
Module 8 :
Advanced Data Handling & Big Data Concepts
- Key Tools: ETL Tools, Spark (Intro), Data Lakes
- Learning Outcomes: Understand ETL pipelines; perform basic big data operations and integrate data from multiple sources.
Highlights
Module 9 :
Statistical Analysis & ML Foundations
- Key Tools: Scikit-learn, Statistical Models
- Learning Outcomes: Apply inferential statistics and regression analysis; understand ML concepts and supervised/unsupervised learning.
Highlights
Module 10 :
Predictive Modeling & Model Optimization
- Key Tools: Scikit-learn, Hyperparameter Tuning Tools
- Learning Outcomes: Build and train predictive models; perform validation and optimization for accuracy.
Highlights
Module 11 :
AI-Powered Data Processing & Explainable AI
- Key Tools: AutoML, SHAP, LIME
- Learning Outcomes: Implement AutoML workflows; interpret and explain ML model outputs.
Highlights
Module 12 :
Business Intelligence (BI) Tools & Dashboards
- Key Tools:Power BI, Tableau, DAX
- Learning Outcomes: Build interactive BI dashboards; perform advanced data storytelling using visual analytics.
Highlights
Advanced AI, Capstone & Industry Readiness
Module 13 :
Advanced AI & Automation
- Key Tools: Web Scraping (BeautifulSoup, APIs), ChatGPT/AI Tools
- Learning Outcomes: Build interactive BI dashboards; perform advanced data storytelling using visual analytics. Use NLP for text analytics; automate data extraction via APIs; integrate AI tools for reporting.
Highlights
Module 14 :
Capstone Project Phase 1 – Data Preparation
- Key Tools:APIs, Python, SQL
- Learning Outcomes: Define project goals; collect and integrate data; ensure data quality and readiness.
Highlights
Module 15 :
Capstone Project Phase 2 – Model Development
- Key Tools: Scikit-learn, AutoML, Power BI
- Learning Outcomes: Conduct EDA; build predictive ML models; integrate AI automation for insights.
Highlights
Module 16 :
Capstone Project Phase 3 & Career Launch
- Key Tools:Power BI, GitHub, Presentation Tools
- Learning Outcomes: Create dynamic dashboards; document and present projects; learn career pathways and emerging AI/analytics trends.
Highlights
Our Distinctive Approach to Data Analytics Certificate
At Win in Life Academy, we offer a cutting-edge Data Analytics program that blends advanced tools, expert guidance, and real-world applications. Our curriculum is thoughtfully designed and mentored by seasoned industry professionals to ensure learners gain practical, future-ready expertise.
Real-World Project Experience
Engage in hands-on projects that bridge theory with practice, replicating real industry scenarios and enhancing problem-solving capabilities.
Expert Mentorship from Industry Leaders
Learn directly from experienced professionals who bring deep market insights and cultivate analytical thinking aligned with evolving industry trends.
Career Advancement Pathways
Benefit from access to an exclusive professional network, connecting you with peers, mentors, and employers for internships, career opportunities, and long-term growth.
Program Fees
New Batches Starts Every 15th & 30th
₹1,50,000 (*Incl. Taxes)
Note: 0% interest rates with no hidden cost
Programme Faculty
What's Unique About This Program?
Why is our Data Analytics the top choice?
Features
Industry-Focused Curriculum
Placement mentorship program
Corporate Etiquette Sessions
Capstone projects
LMS Course kit
EC Council collaboration
Recorded Video
1:1 Personalized Mentorship
Placement Mock Interviews
Interdisciplinary expertise
Industry Expert sessions
WILA
Institute 1
Institute 2
Institute 3
Success Stories
Graduate Perspectives
Win in Life’s Certificate in Data Analytics with AI Foundation + IBM Module
Master the fundamentals of data analytics and AI-driven insights through a structured learning experience that blends expert-led sessions, interactive online classes, and hands-on projects guided by industry professionals.
Connect with our graduates
Have questions? Reach out to our alumni!
Find WILA alumni profiles and know more about their career path, specialisation and more.
(FAQs) FAQs on Data Analyst Certification Program
The Certification in Data Analytics with AI Foundation is a 4-month program that builds essential analytical, technical, and visualization skills. It helps learners master the complete data lifecycle from collection and cleaning to modeling and reporting by using industry-standard tools.
The training combines pre-recorded learning sessions, live instructor-led classes, and guided projects. Each module focuses on practical applications, so learners can confidently analyze data and draw insights relevant to real business problems.
The curriculum includes Python for data analysis, SQL fundamentals, Excel for data management, statistical analysis, Power BI and Tableau for visualization, and AI foundations to help integrate intelligence into analytics workflows.
Yes, the data analytics course online is entirely available, offering flexibility for working professionals and students. Learners can access live interactive sessions, recordings, and project support through Win in Life Academy’s digital learning platform.
This certification emphasizes hands-on learning, AI integration, and real-world datasets. It bridges analytical skills with business understanding, preparing learners for data-driven roles across industries.
This professional data analytics training program is ideal for graduates, working professionals, or anyone seeking to transition into analytics-driven roles. No prior coding experience is required; concepts are taught from foundational to applied levels.
While data analytics bootcamps are often short and intensive, Win in Life Academy’s 4-month certification offers a balanced pace with deeper conceptual understanding, guided mentorship, and structured project-based learning. .
You’ll learn data analytics through a blend of theory and practical exposure and closely working with tools like Excel, Python, SQL, Power BI, and Tableau, while applying techniques such as data cleaning, exploration, and visualization on live datasets.
The data analysis training develops your analytical thinking, statistical understanding, and data interpretation abilities, enabling you to extract meaningful patterns and make evidence-based business recommendations.
Yes, the course introduces key business analytics certification principles that help learners connect data insights with strategic decision-making, performance tracking, and process optimization.
You’ll gain expertise in visualization tools like Power BI and Tableau to design dashboards, communicate findings visually, and tell compelling stories with data.
SQL for data analytics is taught for querying, filtering, and managing structured data efficiently. It’s an essential skill for analysts to access and manipulate databases in real-world projects.
The Python data analytics course is used for data manipulation, statistical analysis, and automation using libraries such as Pandas, NumPy, and Matplotlib. It enhances your ability to perform complex analytics tasks efficiently.
Yes, Excel serves as a foundational analytics tool in the early stages of the program, helping learners understand formulas, pivot tables, dashboards, and basic data modeling.
Learners can pursue roles in data analytics career path such as Data Analyst, Business Intelligence Analyst, Reporting Analyst, or Junior Data Scientist. The certification builds a strong foundation for advanced analytics or AI specialization.
Yes, you’ll gain hands-on experience with Power BI certification for creating reports and dashboards. It prepares you for globally recognized Power BI skill assessments.
Absolutely. The Tableau training course is included to help you visualize and share insights interactively. You’ll work on real-time dashboards to support decision-making scenarios.
This section covers descriptive and inferential statistics, probability, hypothesis testing, and correlation analysis, all essential for understanding data trends and drawing valid conclusions.
Industries such as finance, healthcare, e-commerce, and marketing heavily rely on both data analytics and machine learning and their synergies. The finance industry required fraud detection and algorithm trading, the healthcare industry requires disease prediction and personalize medicine, e-commerce industry requires recommendation systems and customer churn prediction, and marketing industry requires customer segmentation, and ad targeting.
Yes, the later modules focus on advanced techniques like predictive modeling, AI-driven analytics, and data storytelling for strategic business use.
While Data Science focuses on algorithms and model development, Data Analytics emphasizes interpretation, visualization, and actionable insights. This program strengthens your analytical foundation for either path.
By completing this program, you’ll acquire the analytical, technical, and visualization skills required for entry-level data analyst roles, supported by a strong project portfolio.
Yes, it includes guided project work, resume enhancement modules, and exposure to real-world case studies to help you prepare industry expectations. (Note: No placement support is included.)
Projects involve analyzing datasets from finance, retail, healthcare, and marketing to practice visualization, pattern discovery, and reporting on live business scenarios.
It means learning with authentic, industry-grade datasets to simulate real analytical tasks such as cleaning, modeling, and interpreting information just as professionals do.
Yes, upon completion, you’ll receive an industry-recognized certification from Win in Life Academy, validating your practical expertise in data analytics and AI foundations.
