Predesigned Program
Advanced Analytics
Interactive Dashboarding
Business Machine Learning
For Your Leadership And Teams
bring your own data and witness the training outcomes
Why do you need to upskill?
Data is highly valuable digital asset that is only expected to grow over time.
Enterprises are investing heavily in building strong data analytics teams to ensure sustainable growth, but finding appropriate talent to develop customized data-driven solution is a challenge.
There is a significant talent gap, and training existing employees for new skills is advantageous for organizations, as they have domain expertise, making it easier to teach them new skills.
On right, statistics from World Economic Forum are shown [Upskilling Revolutions Is Inevitable!]
Our philosophy for the trainings.
Our pre-designed programs are tailored to meet today’s corporate needs and are highly valued by our clients. Our philosophy, ‘Bring Your Own Data,’ ensures that you and your leadership team can directly see the impact of our solutions. While it requires extra effort on our part, nothing makes us happier than seeing our clients succeed.
Individual program details
data-driven leadership
instructor-led
onsite/remote
Certification
20 hrs
Overview:
This 20 hours [recommended] training equips executives and non-technical leaders with essential skills to harness data for informed decision-making.
Participants will define and leverage Key Performance Indicators (KPIs), understand data’s role in organizational processes, and explore data fluency’s impact on communication and strategic planning.
Through practical workshops and case studies, attendees will gain proficiency in designing and leading data-centric projects, enabling them to drive sustainable business outcomes in this data-driven world.
Business Outcomes:
- Understand and develop data-driven mindset for leadership.
- Define a prioritize KPI’s critical to organizational success
- Integrate data fluency into communication and decision-making processes.
- Create and lead high-performing data-centric teams through collaboration and effective communication
- Identify business problems and their data-centric solutions while implementing ethical guidelines for responsible data use.
Target Audience:
Executives, senior managers, decision makers and professionals seeking to enhance their understanding of data-driven decision- making principles and practices.
Module 1:
Value of Data to an Organization
Explore and examine how data drives growth, efficiency, and competitive advantage by uncovering market trends, enhancing customer experiences, and optimizing operations with real-world examples.
Module 2:
Define Concepts and Roles in Data Project
Learn to build data projects, key roles and their contributions to successful data project outcomes. Conduct a high-level gap analysis for data skills to identify critical roles for hire.
Module 3:
Data Fluency and Communication
Understand the importance of data culture, data fluency, and techniques for improving data literacy. Explore strategies for effectively communicating complex data insights within the organization.
Module 4:
Digital Decisioning and KPIs
Build KPI’s for modern organization and integrate them with digital decision-making tools. Identify and monitoring relevant metrices to align with organizational goals and drive continuous improvements.
Module 5:
Risk and ROI
Examine potential risks, including data privacy and security issues, and learn to calculate and communicate ROI of data projects. Learn to make strategies for balancing risks and benefits to make informed decisions.
modern data foundations
instructor-led
onsite/remote
Certification
20 hrs
Overview:
Introduce your leadership and teams with the fundamental concepts in data management, focusing on relational and non-relational databases, and creating Cloud based data solutions.
Participants will learn database design principles, SQL/T-SQL querying, and how to manage data workloads on Cloud such as Azure.
This training blends theoretical knowledge with practical skills, preparing you and your team to manage and utilize data and optimize business data processes to effectively achieve operational and strategic objectives.
Business Outcomes:
- Understand the importance of data, its sources and consumption in business.
- Use data-driven insights for making strategic decisions and managing projects.
- Create and lead high-performing data science teams through collaboration and effective communication.
- Identify business problems that can be solved using data science and ensure ethical practices while driving successful outcomes.
Target Audience:
Executives, senior managers, professionals in data, analytics and IT landscape seeking to enhance their understanding of modern data storage and engineering strategies for scalable cloud-based data management solutions.
Module 1:
Data Fundamentals and Storage Needs
Learn about the importance of data, its types and sources in businesses. Explore modern data storage technologies and learn to make effective strategies for its secure storage following the best practices for corporate data.
Module 2:
Database Concepts
Explore key concepts and terminologies in databases. Overview design principles, objectives and implement them in your selected organization for effective storage and efficient retrieval of the corporate data.
Module 3:
Building and Managing Databases
Identify subjects, select entities and define keys for establishing relationships and their cardinality. Importance of normalization and schema design. Build and configure cloud databases for data migration and management.
Module 4:
Introduction to SQL/T-SQL
Learn basic querying techniques and common operation to work with data using SQL/T-SQL. Expand you understanding on retrieving data using join operations. Explore the built-in SQL/T-SQL functions.
Module 5:
Cloud Data Solutions
Explore Azure data services and common data workloads. Learn to setup cloud storage, relational and non-relational databases. Build a cloud data architecture for your selected organization in your final project.
leading data science
instructor-led
onsite/remote
Certification
20 hrs
Overview:
Specifically designed for executives in managerial roles who aim to establish and lead data science teams and projects.
The training emphasizes strategic considerations over coding skills.
The participants will develop a profound understanding of data science principles and learn how data-driven insights can significantly impact the organization.
Engaging group exercises and discussions will enable executives to skillfully plan and execute data science initiatives, leveraging their newfound expertise from the program.
Business Outcomes:
- Understand how data science can transform businesses strategically.
- Use data-driven insights for making strategic decisions and managing projects.
- Create and lead high-performing data science teams through collaboration and effective. communication
- Identify business problems that can be solved using data science and ensure ethical practices while driving successful outcomes.
Target Audience:
Executives, senior managers, decision makers and professionals seeking to enhance their understanding of data science principles and practices, enabling them to effectively lead data science teams and projects in their organizations.
Module 1:
Understand The Data Science Myth
Learn about data science, its strategic impact and importance, terminology and how to identifying opportunities for data-driven applications in various industries, group exercise.
Module 2:
Identify Talent Needs and Team Structure
Learn to Build and lead data science teams. Understand data-driven organizational structure, roles and how to hire appropriate data science talent with effective strategies, group exercise.
Module 3:
Identify Pressing Problem and Solution
Learn to Identify and frame business problem for data science solution in your corporate setup. Explore key metrices and success criteria aligned with business objectives, group exercise.
Module 4:
Predict and Plan Your Next Move
Learn to Leverage data for decision-making, EDA, descriptive and diagnostic analytics, Importance of predictive modeling and data driven strategic planning, group exercise.
Module 5:
Risk, ROI and Data Science Projects
Explore principles and methodologies for data science projects. Set goals, milestones and timelines. Explore potential risks, impact and ROI in the business, Group exercise.
LLM leadership advantage
instructor-led
onsite/remote
Certification
20 hrs
Overview:
This high-impact program equips business and technology leaders with unified understanding of Large Language models (LLMs) and how use them to unlock enterprise value.
This intensive training demystifies LLMs, clarifies their business relevance, and prepare leadership to drive AI-enabled transformation and strategy.
Participants will learn how to identify opportunities, evaluate solutions, and guide teams in implementing responsible, ethical, scalable LLM initiatives aligned with strategic objectives.
Business Outcomes:
- Understand how LLMs transform business models, decision-making, and operations.
- Identify high-value opportunities that deliver measurable ROI.
- Bridge communication gap between business and technical teams.
- Apply RAG, fine-tuning, and enterprise architecture concepts to real use cases.
- Strengthen governance, security, and responsible AI practices.
- Build a practical, actionable roadmap for LLM adoption.
Target Audience:
Executives, senior managers, directors, product leaders, strategy teams, and decision makers seeking to deepen their understanding of LLMs and generative AI to guide successful adoption in their organizations.
Module 1:
Demystify LLMs & Generative AI
What LLMs are and how do they work. Foundations, terminology, capabilities and their industry impact. Myths vs realities, and framing AI opportunities. Includes group exercise.
Module 2:
Talent, Architecture & Readiness
Roles, team structure, platform and vendor selection, data readiness, governance, and enterprise LLM architecture fundamentals. Includes group exercise.
Module 3:
Identify High-Value Use Cases & RAG
Identifying and prioritizing impactful business problems and evaluating their feasibility. Designing Retrieval-Augmented Generation (RAG) workflows. Includes group exercise.
Module 4:
Customization & Deployment of LLMs
Customization & scaling in production. Fine-tuning, model evaluation, security, MLOps. Chat-bots, agents & decision-support systems. Deployment considerations. Include group exercise.
Module 5:
Risk, ROI & LLM Strategy Roadmap
Governance, adoption, and leading sustainable transformation. Organizational enablement, milestones, governance, and a 30-60-90 day adoption plan. Group exercise & capstone strategy design.
AI Evals for leadership
instructor-led
onsite/remote
Certification
20 hrs
Overview:
Artificial intelligence is no longer a technical experiment but a leadership decision with strategic, ethical, regulatory, and reputational implications.
This executive-focused course equips leaders with practical AI evaluation frameworks to assess value, risk, data quality, model performance, and lifecycle readiness.
Using real-world examples and deployment monitoring, participants learn to make confident, defensible, and board-ready AI decisions across public and private sector environments.
Business Outcomes:
- Evaluate AI initiatives using a structured, defensible executive framework.
- Align AI investments with strategic and public-value objectives.
- Identify and mitigate ethical, legal, and reputational AI risks early.
- Establish clear governance, oversight, and accountability mechanisms with full control.
- Monitor AI systems post-deployment to ensure sustained performance and trust using right lifecycle metrics.
Target Audience:
Board members, senior executives, public-sector leaders, and technical leaders responsible for approving, governing, or scaling AI initiatives. Designed for decision-makers who must balance strategic value, technical reality, and public accountability.
Module 1:
AI Evals – Leadership & Governance Responsibility
AI failures are leadership failures. Establishes AI evaluation as a core responsibility of executives and boards, not just technical teams. Learn how evaluation protects trust, accountability, and institutional credibility.
Module 2:
Evaluating AI Value, Use Cases & Strategic Fit
Learn how to evaluate that AI initiatives truly serve strategic or public objectives. Focus on prioritization, value-for-money, and outcome-driven decision-making
Module 3:
Data & Model Evaluation
Most AI risks originate in data and models long before deployment. Assess data quality & model performance without needing technical depth. Gain confidence to challenge assumptions and demand evidence.
Module 4:
Risk, Ethics & Regulatory Evaluations
AI systems can amplify risk at scale if not governed responsibly. Focuses on evaluating ethical, legal, and reputational impacts before they become public failures. Embed trust and compliance into AI decisions.
Module 5:
Lifecycle, Monitoring & Evaluation
AI evaluation does not end at deployment, it intensifies. Learn how to monitor AI performance, risk, and drift over time. As an executives, you must learn how to retain control through ongoing oversight and decision gates.
python for data science
instructor-led
onsite/remote
Certification
30 hrs
Overview:
This course is specifically designed for professionals and teams who seek to unlock the power of Python in data science.
Participants will gain practical knowledge with hands-on experience of Python and its powerful libraries within the data science ecosystem.
With strong focus on enhancing data manipulation and analysis skills, the course will empower the participants to effectively leverage Python for data-driven insights and decision-making.
Business Outcomes:
- Proficiency in Python programming covering the fundamental concepts.
- Data manipulation, wrangling and efficient data analysis.
- Improved data management and enhanced productivity using effective utilization of technology and resources.
- Foundation for further growth and automation.
This course includes daily group exercises and hands-on lab sessions along with home-work to reinforce learning objectives. Participants will actively apply Python programming concepts and utilize NumPy and Pandas for data analysis on real-world data.
Target Audience:
Managers, early career professionals and analysts who are interested in utilizing Python for data science applications and develop data analysis skillset.
Module 1:
Learn Required Programming Skill
Set the foundation and learn essentials of Python programming language, setup environment for data science projects.
Module 2:
Data Science Ecosystem in Python
Learn about the tools such as NumPy and pandas, explore their built-in functionalities for data analysis and manipulation.
Module 3:
Make Your Data Meaningful
Understand data cleaning, preprocessing and wrangling using NumPy and pandas, descriptive statistics and data transformation.
Module 4:
Analyze and Visualize Patterns
Exploratory data analysis and visualizations using pandas library’s built-in functionality, understanding patterns and distributions in the data.
Module 5:
Automate, Report and Communicate
Automation, reporting and communicating insights from the data for informed decision making, capstone project.
advanced analytics & interactive dashboards using python
instructor-led
onsite/remote
Certification
60 hrs
Overview:
This course is designed to enhance participant’s knowledge and expertise on advanced analytics, reporting and dashboarding using Python.
Participants will learn advanced techniques in data manipulation and analysis. They will explore how to use SQL within Python for data querying from MySQL databases and create visually appealing and informative plots and interactive dashboards.
The course will cover range of data science libraries including NumPy, pandas, matplotlib, seaborn, MySQL/Python connector, statsmodels etc.
Business Outcomes:
- Gain advanced skills in data manipulation, analysis, and visualization.
- Acquire proficiency in using SQL within Python for data querying.
- Create visually appealing plots and interactive dashboards.
- Apply advanced analytics techniques to uncover patterns, trends, and opportunities within the data.
- Future-ready workforce with advanced skillset.
Target Audience:
Data analysts, Business analysts, and early career professionals seeking advanced skills in data analysis, visualizations, and interactive dashboard development for reporting.
Module 1:
Accessing Database using Python
MySQL databases, database clients, working with SQL queries using Python for retrieving and storing the data into the databases. Group exercise/homework.
Module 2:
Advanced Skills In Data Manipulation
Advanced techniques for data cleaning, preprocessing, wrangling, aggregation, and transformation. Working with missing data, group exercise/homework.
Module 3:
EDA & Business Statistics
Creating customized plots, business statistics, distributions and statistical data visualizations, relationships and patterns in data, group tasks/homework.
Module 4:
Interactive Visualization & Dashboards
Interactive visualization and choropleths. Dashboard and its components. Creating interactive dashboards using Python, group exercise/homework.
Module 5:
Capstone Project To Maximize Learning
Principles and methodologies for reporting data insights,, goals, milestones and timelines, capstone project and final presentation for evaluation.
business machine learning
instructor-led
onsite/remote
Certification
120 hrs
Overview:
This exclusive program is specifically designed for your existing analytic teams, new employees and fresh graduates.
The program present the role of artificial intelligence with hands-on experience in applying machine learning techniques to real-world data.
Participants will learn to preprocess data for machine learning. They will apply various advanced algorithms for predictive modeling and learn techniques to evaluate their performance.
In the capstone project, the participants can apply their skills to your own corporate data for maximum learning and practical application.
Business Outcomes:
- Develop solid understanding of the role of machine learning in data-driven business.
- Gain hands-on experience in end-to-end machine learning projects including risk assessment and customer segmentation.
- Understand the interpretability of machine learning models and how to optimize them.
- Future-ready employees and workforce to take your organization to the next level.
Target Audience:
Data analysts, Business analysts, fresh graduates, and early career professionals who wants to understand the role of AI in the organization and develop practical skills in machine learning for data-driven decision-making.
Module 1:
Introduction to Machine Learning
Learn about machine learning, ethics and fairness in business sector, solidify you understanding by learning about the use cases and start working on your own data to train your first model.
Module 2:
Supervised Machine Learning
Get deeper understanding of supervised machine learning for regression and classification. Explore how these models will help you to solve pressing issues including risk assessment and future planning.
Module 3:
Unsupervised Machine Learning
Understand the importance of clustering techniques and explore how these algorithms can help you learn user behaviour and customer segmentation for effective business strategies.
Module 4:
Present And Deploy Your Best Model In Capstone Project
Bring your own data and train a model to resolve your pressing problem. Learn how to interpret your trained model get the best for your dataset. Deploy your model, create a dashboard or present a report to your leadership and fellows.
time series analysis
instructor-led
onsite/remote
Certification
30 hrs
Overview:
This course is designed for your financial teams and professionals who are interested in gaining a comprehensive understanding of time series data, its analysis and business application.
Participants will explore and learn range of techniques and tools to effectively analyze and interpret time-dependent data, enabling them to make informed decision in a dynamic and evolving industry in this era of digitalization.
Capstone project is included based on “bring your own data” for maximum learning and practical application.
Business Outcomes:
- Enable your employees to effectively analyze time series data for informed decision-making.
- Develop skillset to forecast for your business needs accurately and reliably.
- Enable your team to identify and assess volatility and risk from data and develop risk management strategies.
- Future-ready workforce with skillset in advanced time series analysis techniques for handling complex time dependent data.
Target Audience:
Financial teams, financial analysts, risk managers, quantitative analysts, and anyone involved in time series data analysis for their business needs.
Module 1:
Time Series Data and Python
Develop solid understanding of time series data and its importance in decision making, explore the tools and techniques in Python to process time series data.
Module 2:
Time Series Modeling and Forecasting
Understand the modeling concepts for time series and learn forecasting techniques and how they are implemented with hands-on training using Python.
Module 3:
Seasonality and Trend Analysis
Understand the importance of key features in time series data and how they are impacting business decisions, discuss your business and importance of trends.
Module 4:
Volatility Modeling and Risk Assessment
Learn volatility and risk for your business and how to mitigate them from historical data modeling and forecasting, work with GARCH and ARCH models.
Module 5:
Advance Topics and Capstone Project
Get introduced to the advance topics in time series and learn to evaluate and select appropriate model for your data in the capstone project.
Deep Neural Networks In Day-To-Day Business
instructor-led
onsite/remote
Certification
30 hrs
Overview:
This course will equip the participants with advanced understanding of utilizing deep neural networks for predictive modeling.
Specifically designed for professionals with diverse background across the organization, the course focuses on practical implementation of neural network models for range of business tasks, enabling participants to develop hands-on skills.
Capstone project is included, allowing participants to bring their own data and gain valuable experience in real-world application for maximum learning and practical application.
Business Outcomes:
- Understanding of artificial neural networks and their architectures.
- Enable your employees to effectively develop deep learning models for enhanced and informed decision-making.
- Develop proficiency in your team of implementing various neural networks architectures for risk sentiment analysis, assessment, forecasting, portfolio optimization and much more.
- Develop employees and your workforce capable of advanced skillset for your own business optimization.
Target Audience:
Mid-level professionals and data-related roles, such as advanced analysts, financial and business analysts, risk analysts, marketing and operation managers/analysts. Participants are expected to have a basic understanding of data analysis and business concepts.
Module 1:
Deep Learning & Business Applications
Gain the most valuable knowledge and hands-on skill to work with artificial neural networks, learn about the best available frameworks for their business implementation.
Module 2:
Building & Training Neural Networks
Develop most advanced and trusted deep learning models, help your organization to effectively achieve strategic objectives with hands-on implementation.
Module 3:
Forecast & Understand The Market
Advance your team’s skillset and develop highly trusted artificial neural networks architectures for day-to-day business tasks, including forecasting, churn prediction, personalized service and more!
Module 4:
Deep Learning & Business Optimization
Understand, explain and implement deep learning algorithmic to optimize business, use data-driven strategies and increase your likelihood of winning the world of business.
Module 5:
Capstone Project For Practical Learning
Deploy, monitor and maintain your developed deep learning models, maximize your learning and solidify your skills by working and presenting a capstone project on our own data.
Natural Language Processing (NLP) And Business
instructor-led
onsite/remote
Certification
30 hrs
Overview:
The participants will develop the ability to analyze and extract valuable insights from unstructured textual data, unveiling patterns, sentiment, and customer expectations.
This unique skillset of Natural Language Processing (NLP) will empower your team to make informed decisions with comprehensive understanding of customer behavior, market trends and emerging risks.
The course will enhance the ability of your analysts and help them to drive actionable insights and maximize the potential unstructured data assets of your organization.
Business Outcomes:
- Gain insights from customer feedback and sentiment to enhance customer satisfaction and personalize services.
- Automate manual processes such as document classification and compliance monitoring, saving time and reducing error.
- Leverage NLP techniques and train advanced models to detect and prevent fraud, manage risks, and minimize financial losses.
- Develop an in-house local workforce with advanced NLP skillset for business optimization and data-driven strategies.
Target Audience:
Your employees in marketing and customer service teams and related roles who wants to utilize language data to enhance their daily business operations. Machine learning engineers, Junior data scientists, Data analysts, financial, risk and quantitative analysts in your team.
Module 1:
NLP, Business & Python
Learn about the importance and role of language data in business,. Role of Python in preprocessing such complex NLP data. Gain understanding of machine learning in the context of NLP.
Module 2:
Know Your Customer’s Sentiment
Develop a skillset to mine the text such as customer feedback to understand your customer’s behaviour and provide personalized business service for retention and relationship building.
Module 3:
Capture The Context in Textual Data
Learn state-of-the-art pre-trained models for words embedding and capture the context of the text. Train machine learning models with word embeddings for enhanced performance.
Module 4:
Text to Streamline Operations
Develop document classification and claim sorting algorithms. Automate compliance monitoring and enhance business decisions, Build NLP driven business and risk management strategies.
Module 5:
Capstone Project
Maximize your learning and solidify your skills by working and presenting a capstone project, you chance to bring your own data for valuable experience or work with the given one.
Mastering Power BI
instructor-led
onsite/remote
Certification
30 hrs
Overview:
This course is to empower your non-IT professionals to excel in data-driven decision-making.
The participants will learn to create BI solutions with Power BI and develop reports and dashboards independently to fulfill your business data needs.
They will master the solution development and complex problem-solving by applying rules, organize data models, and visualize with charts, graphs, maps, and gauges.
To maximize the learning, the participants will deploy a solution dashboard to Power BI Service and make it accessible across devices.
Business Outcomes:
- Enhance data-driven decision making by equipping your employees to excel in advanced analytics.
- Automate manual processes and streamline business insights by developing seamless live BI dashboards.
- Develop data transformation skillset in you employees to effectively use data for BI solutions.
- End-to-end solution development and deployment using Power BI service.
Target Audience:
Your analytic teams and non-technical employees across the organization who are aiming to create self-service BI solutions and reports. Basic understanding of database terminology is preferred however it is not required.
Module 1:
Storytelling & Data Connection
Learn the skillset to establish connection links between Power BI and range of data source and weave a coherent story that presents insights, highlights trends and suggest data-driven actions.
Module 2:
Data Transformation in Power Query
Develop a skillset to refine and reshape data from disparate sources using power query. With hands-on training, transform and structure your data to generate appealing visualization.
Module 3:
Data Modelling & DAX
Harness the power of Data Analysis Expressions (DAX) to develop robust data models. Architect efficient relationships, calculations and measures in Power BI to convert data into success stories.
Module 4:
Reporting & Interactive Visualizations
Harness the power of reporting data insights by developing compelling and interactive reports. Create visuals like geographical, categorical, and time-series to present an actual story to decision-makers.
Module 5:
Power BI Service & Capstone Project
Delve into collaboration, sharing and publishing your unique work using Power BI’s cloud-based capabilities. Bring you own data and maximize your learning by presenting your work as a final project.
Microsoft Fabric For Data Engineering And Analytics
instructor-led
onsite/remote
Certification
60 hrs
Overview:
This course offers essential skills to design, build, and optimize data solutions in Microsoft Fabric.
Focusing on Fabric’s unified data analytics and engineering platform, participants will learn best practices for data ingestion, transformation, storage, and governance.
Each module includes hands-on labs and exercises for practical experience in real-world applications.
By the end of this course, attendees will be ready to implement efficient workflows, ideal for corporate and large-scale data environments seeking modern end-to-end data engineering solutions.
Business Outcomes:
- Build and manage scalable dataflows and secure data pipelines.
- Design ETL/ELT workflows for enterprise-scale data transformation.
- Leverage real-time data processing to ensure reliability and business continuity.
- Optimize data operations for performance efficiency and cost control.
- Maintain compliance and governance across all your data assets in Fabric.
Target Audience:
Data engineers, ETL developers, Data architects, and IT professionals who are seeking to advance their Azure-based data engineering capabilities in corporate or large-scale data environments.
Module 1:
Introduction To Microsoft Fabric
Learn Microsoft Fabric and its data services ecosystem which is foundational for modern data engineering and analytics. Explore essentials for cloud-based solutions.
Module 2:
Data Ingestion & Storage Solutions
Explore and learn about the best practices and efficient data ingestion and storage strategies critical for handling large datasets at scale in Fabric ecosystem.
Module 3:
Data Transformation & Processing
Master data transformation techniques to prepare data for analytics and operational insights. Explore big data tools for data wrangling and enrichment.
Module 4:
Pipeline Orchestration & Real-Time Data
Implement pipeline automation and monitoring for continuous, reliable data flow. Work with real-time data and follow the best practices for pipeline management.
Module 5:
Optimization Strategies & Project
Learn optimization techniques and proven strategies to enhance performance and compliance. Develop a corporate solutions and present in Capstone project.
Database Clients And Python
instructor-led
onsite/remote
Certification
30 hrs
Overview:
Python is a fundamental language for development and data science today. This intensive and immersive training is designed to equip participants with the knowledge and skills necessary to effectively work with widely used MySQL databases using Python.
Participants will learn how to connect to the database, perform common database operations, retrieve and manipulate data, work with multiple tables, and apply advanced database concepts.
The course combines hands-on exercises, practical examples, and real-world projects to ensure participants gain practical experience in SQL with Python.
Business Outcomes:
- Seamlessly connect Python applications to MySQL databases.
- Write and execute SQL queries in Python to retrieve, manipulate, and manage data.
- Implement advanced database features such as stored procedures, triggers and connection pooling to improve the performance and security of your data-centric application.
- Develop the skills necessary to build data-driven applications and effectively achieve strategic objectives.
Target Audience:
Your analytic and database teams, employees in data related roles, junior data scientists and analysts, data engineers and developers. Participants are expected to have a basic understanding of databases, structure query language (SQL) and Python.
Module 1:
SQL, MySQL & Python Integration
Overview of relational database management system (RDBMS), SQL, Python. Setting up environment and establish connection to execute SQL queries from Python. Basic error handling and troubleshooting.
Module 2:
Data Retrieval & Manipulation
Retrieve data from the database using Python and learn to filter and sort the records. Insert, update and delete records in the database using Python. Work with datetime data and SQL functions using Python.
Module 3:
Working with Multiple Tables
Harness the power of SQL, Python and database clients to work with multiple tables using join operations for your Python based data-centric application. Understand database relationships, keys, constraints and normalizations.
Module 4:
Advanced Topics & Optimization
Work with stored procedures and triggers to seamlessly run your data-centric application. Apply optimization techniques, create and work with connection pools to improve security and performance of your application.
Module 5:
Best Practices & Capstone Project
Review and apply best practices for database and Python integration to secure and improve application performance. Work with your own data and maximize your learning by presenting your work as a final project.