Overview

Suitable for

The xMBA program is an innovative, non-theoritical, ​fast-track MBA focusing only on experiential learning ​– to provide the first work experience for students by ​working on hands-on projects from top companies.

Key info

Duration: 3 months (+ optional Externship)

Commitment: 3-5hrs per week

Mode: Online and Flexible

Start date: Batches start on 1st of every month

• Aspiring Leaders: Professionals aiming to fast-track ​their careers into management with hands-on ​experience.
• Career Shifters: Individuals transitioning from non-​management roles into business leadership positions.
  
• Working Professionals: Those wanting to upskill in ​specialized areas while balancing their current job.
  
• Entrepreneurs: Future business owners seeking ​practical training and mentorship to build their ​companies.
  
• Students/Recent Graduates: Job seekers looking to ​enhance their resumes with practical, domain-specific ​work experience
  
• MBA students: Students who are already in an MBA ​program but wish to gain first work experience
  

Program structure

• Product Management
  
• AI Product Development
  
• Digital Marketing
  
• AI in Marketing
  
• Business Development ​& Sales
  
• AI Fundamentals
  
• Data Analysis
  
• Hubspot CRM

Compulsory module

Product Management - 8hrs

Module 1

Module 2

• Product management overview
  
• A day in the Life of a Product Manager
  
• Types of Product Managers
  
• Product lifecycle
  
• Product phases
  
• Types of Innovation
  
• Big picture - Customer-centric innovation
  
• Lean methodology
  
• Principles of lean product development
  
• Jobs to be done methodology
  
• Lean startup canvas
  

Module 3

• Types of Innovation
  
• Customer-centric innovation - Front end of ​innovation
  
• Trend analysis
  
• Trend reports, Delphi study
  
• Opportunity analysis
  
• Idea generation
  
• Creativity techniques
  
• Market research tools
  

Module 4

• Ideal Customer Profile
  
• Personas
  
• MVP - Minimum Viable Product
  
• Components of MVP
  
• Types of MVP
  
• Building MVP using several tools
  
• Pitfalls
  
• Tool intro: Canva
  
• Tool intro: Trello
  
• PRD - Product Requirements Document
  

• Product strategy
  
• SCRUM - Agile methodology
  
• Prioritization techniques
  
• KPIs and Metrics - how and what to measure
  
• Pivot principles
  
• Working with engineers, designers, executives
  
• Tool intro: JIRA,
  
• Tool intro: Trello
  
• Tool intro: Google Analytics
  
• Tool intro: Hotjar
  

Trainers

Quirin Blendl

Cologne, Germany

Founder of 2 startups in Germany, Business ​Coach, Chief Executive Officer at Moyyn and ​has 15+ years of experience in Venture Building, ​Talent Acquisition, and Business

Aravinth Palaniswamy

Berlin, Germany

Founder of 2 startups in Germany and India, ​Technology Consultant, and Chief Product ​Officer of Moyyn, and has 10+ years of ​experience in Venture Building, Product and ​Growth Marketing

Compulsory module

AI Product Development - 4hrs

Modules

• Market analysis for AI products
  
• Defining business objectives
  
• AI Products Landscape
  
• Customer-centric approach to AI Product ​Strategy
  
• AI in Product Roadmaps
  
• Scalability
  
• Risk management
  
• ICP and Personas for an AI product
  

Trainers

Dr. Chetana Didugu

Munich, Germany

Experienced Data Scientist, Product Owner, and ​PhD graduate from IIM Ahmedabad and has ​worked 10+ years in various top companies in ​the world like Amazon, FLIX, Zalando, HCL.

Aravinth Palaniswamy

Berlin, Germany

Founder of 2 startups in Germany and India, ​Technology Consultant, and Chief Product ​Officer of Moyyn, and has 10+ years of ​experience in Venture Building, Product and ​Growth Marketing

Compulsory module

Digital Marketing - 8hrs

Module 1

Module 2

• Customer acquisition funnel
  
• Types of business models
  
• Funnel vs Flywheel approach
  
• Market research methods
  
• Creating ICPs and Personas
  
• Value Matrix
  
• Understanding terms: Lead, Opportunity, MQL, ​SQL, etc
  
• Real world examples of funnels
  
• Go-to-market strategies
  
• Hubspot CRM Tool intro
  

Module 3

• Setting SMART goals
  
• Target audience profiling
  
• Digital Marketing Strategy
  
• Website, Blog and landing page fundamentals
  
• Understanding website structure
  
• Landing page builders (Hubspot, Canva)
  
• Google Analytics, Hotjar
  
• SEO fundamentals: Technical SEO, Local SEO, On-​page SEO, Off-page SEO, etc
  
• SEO research via Spyfu, Nielpatel
  
• Social media marketing & Buffer/Scheduling tools
  

Module 4

• Performance marketing fundamentals
  
• Linkedin ad fundamentals
  
• Types of ads, objectives, and bidding strategies
  
• Creatives strategy
  
• Measurement and optimization
  
• Advanced targeting approaches
  
• Creating LinkedIn ad via campaign manager
  
• META (Facebook, Instagram) ad fundamentals
  
• Creating an ad in META Ad manager
  
• Audiences creation, targeting approaches and ​bidding strategies
  

• Understanding Google Ads
  
• Types of ads
  
• Account structure
  
• Components of Google Ads
  
• Bidding
  
• Keyword research via tools
  
• Optimization
  
• Practical example
  
• Email marketing strategy
  
• Email marketing tools - Mailchimp, Hubspot
  
• Lead generation via tools - Rocketreach
  

Trainer

Aravinth Palaniswamy

Berlin, Germany

Founder of 2 startups in Germany and India, ​Technology Consultant, and Chief Product ​Officer of Moyyn, and has 10+ years of ​experience in Venture Building, Product and ​Growth Marketing

Compulsory module

AI in Marketing - 4hrs

Modules

• AI for Content Creation
  
• AI for Branding
  
• AI for Communications
  
• AI for Design
  
• AI for Social Media
  
• AI for Performance Marketing
  
• AI for Email Marketing
  
• Creating custom GPTs
  

Trainer

Aravinth Palaniswamy

Berlin, Germany

Founder of 2 startups in Germany and India, ​Technology Consultant, and Chief Product ​Officer of Moyyn, and has 10+ years of ​experience in Venture Building, Product and ​Growth Marketing

Compulsory module

Business Dev & Sales - 8hrs

Module 1

Module 2

• ales Pitch & Product Knowledge
  
• Importance of an effective sales deck
  
• Structuring your sales deck
  
• How to create a story
  
• Visuals & Design
  
• Storytelling techniques
  
• Practicing your pitch
  
• Understanding the Product - advantages & ​features
  
• Understanding competition
  
• Crafting the perfect sales pitch (introduction, ​problem identification, solution presentation, ​benefits, call to action)
  
• Putting the customer first
  

Module 3

• Creating a sales deck
  
• Samples of sales decks
  
• How to optimize the slides
  
• Creating a story around the deck
  
• Effective communication
  

• Creating a sales strategy
  
• Goals, Market, USP
  
• Sales goals and forecasting
  
• Target market and audience segmentation
  
• Competitor analysis
  
• SWOT analysis
  
• Sales Channels, Funnel, Tactics
  
• Marketing Qualified Leads
  
• Sales Qualified Leads
  
• Google Analytics, Looker Studio
  
• Tools, Metrics and Development
  
• Work with Hubspot CRM
  

Trainer

Quirin Blendl

Cologne, Germany

Founder of 2 startups in Germany, Business ​Coach, Chief Executive Officer at Moyyn and ​has 15+ years of experience in Venture Building, ​Talent Acquisition, and Business

Compulsory module

AI Fundamentals - 6hrs

Module 1

Module 2

• Importance of AI
  
• AI Fundamentals
  
• AI Applications - NLP, Speech recognition, ​Predictive analysis, Chatbots, Facial recognition, ​Expert systems, Gaming, Healthcare, etc
  
• Machine Learning Essentials
  
• Importance of Data and Data Processing
  
• Model Training
  
• Ethical Considerations
  
• Advancements in AI
  

Module 3

• Supervised Learning Models: Classification
  
• Various types of classification models for binary ​and multi-class classification
  
• Performance metrics: Confusion Matrix, F1, ​Precision, Recall, Accuracy - which one to use in ​which case, with examples
  
• Unsupervised Learning: Clustering, performance ​metrics
  

• Model Improvement Methods
  
• What does model improvement mean? What are ​the different options at our disposal and when to ​use them?
  
• Feature Selection and Dimensionality reduction ​methods: Lasso Regression, Ridge Regression, PCA
  
• Hyperparameter Tuning: Various methods, deep ​dive into Grid-search and Random-search
  
• Cross-Validation
  
• Application to hyperparameter tuning
  

Trainer

Dr. Chetana Didugu

Munich, Germany

Experienced Data Scientist, Product Owner, and ​PhD graduate from IIM Ahmedabad and has ​worked 10+ years in various top companies in ​the world like Amazon, FLIX, Zalando, HCL.

Compulsory module

Data Analysis - 8hrs

Module 1

Module 2

• Introduction to the field of Data Analysis
  
• How to build an Analyst's mindset
  
• An insight into the day-to-day tasks of a Data ​Analyst
  
• Introduction to Descriptive Statistics
  

• Terminology: Sample, Population, Statistic and ​Parameter
  
• Classification
  
• Prediction, Association
  
• Pattern recognition
  
• Descriptive statistic
  
• Measures of Central Tendency and Dispersion
  
• Introduction to data visualisation using Python
  
• Univariate graphs, bi-variate graphs, and when to ​use which
  
• Code Example
  

Module 3

Module 4

• Predictive Analytics
  
• Introduction to Predictive Analytics and various ​predictive tasks
  
• Introduction to Machine Learning, with examples ​of how each applies to real-life predictive ​analytics tasks
  
• Deep Dive into supervised (regression and ​classification) and unsupervised tasks
  
• Code Example using unsupervised learning models ​which ties to Task 1
  

• Inferential Analytics/Statistics
  
• Sample vs Population
  
• What is a Hypothesis: Null and alternate ​hypothesis, test statistic and how to frame a ​hypothesis for your test
  
• Normality and Central Limit theorem: Application ​to hypothesis testing and inference
  
• Types of test statistics
  
• How to perform the hypothesis test, p-value, ​Statistical Power, alpha (confidence), Hypothesis ​Rejection and Failure to Rejection
  
• Impact of sample size on confidence and ​statistical power
  
• Code Example
  

Trainer

Dr. Chetana Didugu

Munich, Germany

Experienced Data Scientist, Product Owner, and ​PhD graduate from IIM Ahmedabad and has ​worked 10+ years in various top companies in ​the world like Amazon, FLIX, Zalando, HCL.

Compulsory module

Hubspot CRM - 8hrs

Module 1

Module 2

• CRM Fundamentals
  
• Hubspot intro
  
• Setting up an account and Navigating the ​dashboard
  
• Adding Contacts - Manual entry
  
• Importing contacts
  
• Organizing Contacts
  
• Creating lists and segments
  
• Using filters for targeted views
  
• Creating Deals
  
• Understanding deal stages
  
• Associating deals with contacts
  
• Managing Tasks, Setting tasks and deadlines
  
• Integrating tasks with your calendar
  

• Emails management
  
• Templates for 1-1 emails
  
• Creating a simple email
  
• Adding in user activity
  
• Chatflows
  
• Marketing Hub
  
• Regular and Automated emails
  
• Website
  
• Landing page creation
  
• Blog creation
  
• Files
  
• Uploading files
  
• CTA creation
  
• Forms
  

Trainer

Specialization Modules

Students can opt for one specialization with live ​task reviews with coaches

Specialization module

Data Science - 8hrs

Module 1

Module 2

• Introduction to the field of Data Science
  
• How to build a Data Scientist's mindset
  
• Data Science approach
  
• Supervised Models: Regression
  
• Code Example
  

• Supervised Learning Models: Classification
  
• Various types of classification models for binary ​and multi-class classification
  
• Performance metrics: Confusion Matrix, F1, ​Precision, Recall, Accuracy - which one to use in ​which case, with examples
  
• Unsupervised Learning: Clustering, performance ​metrics
  
• Code Example
  

Module 3

• Model Improvement Methods
  
• What does model improvement mean? What are ​the different options at our disposal and when to ​use them?
  
• Feature Selection and Dimensionality reduction ​methods: Lasso Regression, Ridge Regression, PCA
  
• Hyperparameter Tuning: Various methods, deep ​dive into Grid-search and Random-search
  
• Cross-Validation
  
• Application to hyperparameter tuning
  
• Code Example
  

Module 4

• Introduction NLP with various common NLP tasks
  
• How is Natural Language data different from Panel ​or Tabular Data?
  
• Steps for processing natural language inputs: NLP ​pipeline (Tokenisation, Stopword Removal, ​Stemming, Lemmatisation)
  
• Various methods of word embedding: Bag of ​Words, Word2vec, Glove, and using Large ​Language Models
  
• Brief introduction to Recurrent Neural Networks ​and Long Short Term Memory models, the building ​blocks for all LLMs
  
• Pre-trained models and transfer learning
  
• Code example
  

• Pandas, Numpy, Python ​functions
• Kaggle notebooks, ​Google colab
• Matplotlib, seaborn, nltk, ​re Scikit learn, XGBoost, ​LightGBM
• Transformers, and many ​more ML packages and ​libraries
• Model metrics: cross ​entropy, DB Index
• NLP, and LLMs for ML ​tasks (hugging face ​library)

Trainer

Dr. Chetana Didugu

Munich, Germany

Experienced Data Scientist, Product Owner, and ​PhD graduate from IIM Ahmedabad and has ​worked 10+ years in various top companies in ​the world like Amazon, FLIX, Zalando, HCL.

Specialization module

Recruitment & AI - 12hrs

Module 1

Module 2

• Talent acquisition manager role definition
  
• A day in the life of a talent acquisition manager
  
• The recruitment funnel
  
• Hiring metrics
  
• Tools for forecasting workforce needs
  
• Types of contracts
  
• Talent acquisition landscape
  
• Job design
  
• Job characteristics model
  

• Types of sourcing platforms
  
• Google for jobs
  
• Linkedin jobs
  
• Indeed
  
• Wellfound
  
• Job Aggregators
  
• Reverse job platforms
  
• Freelancer platforms
  
• Social media platforms
  
• Multiposting platforms
  

Module 3

Module 4

• Active sourcing fundamentals
  
• Active sourcing vs Traditional recruiting
  
• Building an active sourcing strategy
  
• Active sourcing platforms
  
• Rules and Best practices
  
• Active sourcing automation
  
• Xray search and relevant tools
  
• Tool intro: Linkedin recruiter
  
• Tool intro: Github sourcing
  

• Introduction to ATS - Applicant Tracking System
  
• Demo - Workable ATS
  
• Demo - Moyyn ATS
  
• How to screen CVs
  
• Interviews and bias
  
• Handling red flags
  
• Effective screening process
  
• Interview tools like Willo
  
• Creating a sourcing strategy
  
• AI in recruiting
  

Trainer

Aravinth Palaniswamy

Berlin, Germany

Founder of 2 startups in Germany and India, ​Technology Consultant, and Chief Product ​Officer of Moyyn, and has 10+ years of ​experience in Venture Building, Product and ​Growth Marketing

Specialization module

Full-stack

development - 12hrs

Module 1

Module 2

• Introduction to web development
  
• Basics of Front-end development
  
• Basics of Back-end development
  
• OOPS concepts
  
• Software development lifecycle
  
• SCRUM principle
  
• Agile software development
  
• Lean development
  

• Front-end development fundamentals
  
• HTML
  
• CSS
  
• Javascript
  
• Front-end libraries
  
• Frameworks
  

Module 3

Module 4

• Back-end development fundamentals
  
• Java
  
• Spring MVC
  
• IoC
  
• APIs
  
• Building an API
  

• Basics of databases
  
• Basics of SQL
  
• CRUD Operations
  
• Integration and Deployment
  
• REST API
  
• Version control
  
• Build and deployment
  

Trainer

Sharaniya Markandan

Berlin, Germany

Software Engineering Manager with 13 years of ​expertise from leading companies like Ecosia, ​Thomson Reuters, Robert Bosch, Wipro, and ​Deutsche Bank, Sharaniya is a seasoned ​professional in software development, leading ​technical high-performing teams, driving ​successful projects defining project scope, ​managing resources, and delivering on schedule ​and within budget.

Specialization module

Cybersecurity - 16hrs

Module 1

Module 2

• Theoretical information on cybersecurity
  
• Demonstration of cyber security technologies in ​practice
  
• Cyber security technologies, and precautions to ​be taken
  
• Teams in cybersecurity: Red, Blue and Purple ​team applications
  
• Theoretical framework and practical ​demonstration of cyber-attacks
  
• Network and endpoint security technologies with ​hands-on Labs
  
• NIST, CIS, HIPAA, GDPR, PCI-DSS compliance ​topics with hands on LABs
  

• Risk and Vulnerability management with hands-on ​LABs.
  
• Cyber Open-Source Intelligence "OSINT" with ​hands-on LABs.
  
• Cryptography with applications and LABs
  
• Security Log analysis with LABs.
  
• SPLUNK, NESSUS, MALTEGO, SIMPLE-RISK, PF-​ENSE, ZAP-PROXY, NMAP and many other industry ​standard cyber security tools and software’s
  
• Essentials of malware analysis with applications
  
• Endpoint security hardening with applications
  

Module 3

Module 4

• Data and application security
  
• Social engineering and testing awareness with ​Phishing campaigns. How to deploy these ​campaigns with phishing software. (Hands-on)
  
• Hunting cyber attackers with honeypots. (Hands-​on)
  
• VPN for security and privacy. (Hands-on)
  

• SOC operations
  
• Essentials of pen testing
  
• Essentials of Adversary emulation & Cyber Kill ​Chain
  
• Security Controls
  
• Network security protocols
  
• Network protocols
  
• URL filtering with applications
  
• Mobile device security
  

Trainer

Karthik Kulkarni

Bengaluru, India

Cybersecurity expert with 9+years of ​experience in LAN, WAN, Routing, Switching, ​Network security, proxy, SIEM, SOAR, endpoint ​and Information Security domain. Adaptive ​learner and a team player familiar with various ​geographies, including APAC, EMEA and NA-GB ​regions. Worked with top companies like HCL, ​Trane Technologies, Optiv, Dimension Data, etc

Specialization module

NLP & LLM - 8hrs

Module 1

Module 2

• Introduction to NLP
  
• Applications of NLP and significance.
  
• Text Preprocessing
  
• Cleaning and preparing text data
  
• Tokenization
  
• Stemming
  
• Lemmatization
  
• Stop word removal
  
• Code examples
  

• Text Representation
  
• Bag-of-Words (BoW) model
  
• TF-IDF (Term Frequency-Inverse Document ​Frequency)
  
• Introduction to Language Models
  
• Understanding concepts of n-grams
  
• Markov models
  
• Code examples
  

Module 3

Module 4

• Introduction to Machine Learning for NLP
  
• Supervised Learning in NLP
  
• Basics of text classification and sentiment ​analysis using machine learning algorithms (e.g., ​Naive Bayes, SVM)
  
• Unsupervised Learning in NLP
  
• Clustering techniques like K-means for text data ​and topic modeling with techniques like LDA ​(Latent Dirichlet Allocation)
  
• Code examples
  

• Advanced NLP Concepts and Applications
  
• Deep Learning in NLP with Large Language Models
  
• Introduction to neural networks for NLP tasks
  
• Special RNNs: LSTMs
  
• BERT
  
• Encoders and Decoders to Autoencoders
  
• Introduction to the concept of Attention
  
• Real-world Applications using LLMs
  
• Application 1: Named Entity Recognition
  
• Application 2: Parts of Speech Tagging
  
• Application 3: Question- Answering (Text ​Similarity)
  
• Application 4: Topic Modelling
  
• Application 5: Text Summarisation
  
• Application 6: Text Generation
  

Trainer

Dr. Chetana Didugu

Munich, Germany

Experienced Data Scientist, Product Owner, and ​PhD graduate from IIM Ahmedabad and has ​worked 10+ years in various top companies in ​the world like Amazon, FLIX, Zalando, HCL.

Specialization module

Gen AI & Prompt

Engineering - 8hrs

Module 1

Module 2

• Introduction to Neural Networks
  
• Introduction to Perceptron
  
• NN terminology
  
• Forward and Backward Propagation
  
• Code Example: Simple neural network ​implementation using a framework like ​TensorFlow
  

• Introduction to generative models
  
• Importance and applications in various industries.
  
• Examples of generative models
  
• GANs
  
• VAEs
  
• Code example
  

Module 3

• Training and Evaluation of GANs
  
• Techniques for training stable GANs
  
• Evaluation metrics for assessing the quality of ​generated samples.
  
• Code example
  

Module 4

• Practical use-cases of generative networks (Gen ​AI)
  
• Importance of Gen AI in content creation
  
• ChatGPT revolution: introduction to chatGPT and ​how to use it
  
• NLP: chatGPT, content creation, text ​summarisation, tone assignment, teaching, etc. ​using ChatGPT
  
• Pitfalls: Hallucinations, temperature- a measure of ​randomness, and the tenets of clean prompt ​engineering
  
• Introduction to Prompt Engineering
  

Trainer

Dr. Chetana Didugu

Munich, Germany

Experienced Data Scientist, Product Owner, and ​PhD graduate from IIM Ahmedabad and has ​worked 10+ years in various top companies in ​the world like Amazon, FLIX, Zalando, HCL.

Specialization module

IT System

Administration - 12hrs

Module 1

Trainer

• IT Fundamentals
  
• Networking Fundamentals
  
• Windows Introduction
  
• Windows Installation methods and Deployment ​Tools
  
• User Managment from WorkGroup and Domain
  
• Post-installation Configuration and Personalization
  
• Configuring Storage, Data Access and Usage
  

Module 2

• Windows Defender
  
• Windows Backup and Restore
  
• Deploy Windows client
  
• Manage identity and compliance
  
• Manage, maintain, and protect devices
  
• Manage applications
  
• AZ-900
  

Rakshith Kulkarni

London, UK

Cybersecurity expert with 9+years of ​experience in LAN, WAN, Routing, Switching, ​Network security, proxy, SIEM, SOAR, endpoint ​and Information Security domain. Adaptive ​learner and a team player familiar with various ​geographies, including APAC, EMEA and NA-GB ​regions. Worked with top companies like HCL, ​Trane Technologies, Optiv, Dimension Data, etc