Instruction
390+ hours of live, instructor-led sessions delivered across 6 months, with no pre-recorded video substitution for core content.
AI Engineering and Machine Learning Fellowship
A 6-month fellowship covering machine learning, deep learning, natural language processing, and generative AI. Fellows build and deploy five AI products under the mentorship of ExpertsPro's engineering team.
Machine Learning & Deep LearningAI Agents & LLM AppsReal Work Experience
6 MonthsDuration (internship/project)
390+Hours of Live Instruction
1:8Mentor-to-Student Ratio
Online & OfflineAvailable Tracks
CertifiedCo-branded with ExpertsPro
Technologies You'll Master
Programming & Machine Learning
Python
NumPy
Pandas
Scikit-learnPythonNumPyPandasScikit-learnPythonNumPyPandasScikit-learn
PythonNumPyPandasScikit-learnXGBXGBoost
PythonNumPyPandasScikit-learnXGBXGBoost
PythonNumPyPandasScikit-learnXGBXGBoost
Deep Learning & NLP
TensorFlow
PyTorch
HFT
OpenCVTensorFlowPyTorchHFTOpenCVTensorFlowPyTorchHFTOpenCV
TensorFlowPyTorchHFTOpenCVTensorFlowPyTorchHFTOpenCVTensorFlowPyTorchHFTOpenCVGenerative AI & Deployment
LangChain
Docker
FastAPILangChainDockerFastAPILangChainDockerFastAPI
GPTOpenAI API
LangChainVDBVector Databases
DockerFastAPIAWSAWS SageMaker
GPTOpenAI API
LangChainVDBVector Databases
DockerFastAPIAWSAWS SageMaker
GPTOpenAI API
LangChainVDBVector Databases
DockerFastAPIAWSAWS SageMaker
CURRICULUM MODULES
This module establishes the programming and data-handling skills required before any machine learning work begins. Fellows work with real datasets from the first week, learning to clean, structure, and interpret data the way it is used in production systems rather than in isolated exercises.
- Python for Data Science
- NumPy and Pandas
- Data Cleaning and Wrangling
- Exploratory Data Analysis
- Statistics and Probability for Machine Learning
- SQL for Data Extraction
PythonData CleaningEDAStatisticsSQL
Program Journey
FoundationWeeks 1 to 4
- Python programming and data handling
- Statistics and probability fundamentals
- First graded assessment at end of stage
Core MLWeeks 5 to 8
- Supervised and unsupervised learning applied to real datasets
- Model evaluation and hyperparameter tuning
- First individual project: a predictive model built end to end
Deep LearningWeeks 9 to 12
- Neural networks, computer vision, and sequence models
- Introduction to transformer-based language models
- Second individual project: an image or text classification system
GenAI & LLMsWeeks 13 to 16
- Retrieval-augmented generation and AI agent development
- Vector database implementation
- Third project: a working RAG chatbot
MLOpsMonth 5
- Model deployment, monitoring, and CI/CD pipelines
- Cloud deployment using AWS SageMaker
- Fourth project: an end-to-end MLOps pipeline
CapstoneMonth 6
- 2-month enterprise-style capstone project
- Direct mentorship from ExpertsPro engineers
- Fifth and final project: a deployed flagship AI product
What This Program Covers
Deployment, Not Only Model Building
Fellows deploy five AI systems during the program, including a retrieval-augmented generation chatbot and an MLOps pipeline, in addition to building and evaluating models.
Curriculum Developed by ExpertsPro's Engineering Team
The program content and mentorship are developed and delivered by ExpertsPro's enterprise AI engineering team.
Coverage of Generative AI and Large Language Models
A dedicated module covers generative AI, large language models, and AI agents, in addition to standard machine learning topics.
Mentor-to-Student Ratio of 1:8
Each mentor works with a defined group of fellows throughout the program, allowing consistent tracking of individual progress.
Defined, Score-Based Placement Pathway
Placement outcomes are tied directly to final program scores: guaranteed placement, placement assistance, or certification, as outlined in the placement policy.
Program
Commitment
What every enrolled student is promised, in writing — the teaching hours, the mentorship coverage, and a defined pathway to an outcome.
Mentorship
1:8 mentor-to-student ratio maintained for the full duration of the program, including the 2-month capstone internship.
Outcome Pathway
A placement pathway defined by final program score: guaranteed placement, placement assistance, or certification and alumni access.
Exclusive Career Services, With a Personalized Career Plan
Get access to KodoWorks’ career services that help you use your skills from this program to move toward your next role.
Interview Preparation
1:1 interview preparation including mock interviews focused on AI and machine learning technical rounds.
Soft Skills Training
Soft skills training paired with pre-assessment and post-assessment technical evaluation.
Hiring Network Access
Access to ExpertsPro's hiring network as part of the program's score-based placement pathway.
Profile Building
Guidance on building a strong AI/ML portfolio, including GitHub, Kaggle, LinkedIn, and resume preparation.
Mock Assessments
A series of mock assessments and structured interview preparation sprints for AI and machine learning roles.
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Frequently Asked Questions
What is the structure of the Fellowship Program in NextGen Data Analytics & Data Science with AI?
×The Fellowship Program is structured into multiple hands-on sprints that build Data Analytics and Data Science skills step by step. The curriculum covers Excel, SQL, Python, data visualization, and practical analytics, and progresses to statistics, machine learning, and AI-driven workflows—ensuring end-to-end, real-world data expertise.