6 month
6 month
6 month
Learn Python, statistics, data analytics, Machine Learning, Deep Learning, NLP, Generative AI and model deployment through practical projects.
18 curriculum modules Hands-on security labs Python + Data Science + AI Academic credit programme**Confirm the awarding details, applicable 40 academic credits and individual admission conditions with Insta Infotech before enrolment.
Build a practical foundation in coding, data acquisition, data preparation, statistical analysis and AI engineering. Progress from exploratory analysis to machine learning, deep learning, natural language processing and deployment.
Explore Python, statistics, SQL, data analytics, machine learning, NLP and AI deployment. Practical testing should be performed only in permitted lab environments.
Build Python, computational thinking, and software development foundations.
Collect, clean, analyse and visualise data to uncover useful business insights.
Explore machine learning, deep learning, NLP and generative AI applications.
Develop data pipelines, dashboards, models and deployment-ready projects.
Explore the complete learning path across Python development, data engineering, SQL, analytics, visualisation, Machine Learning, Deep Learning, Generative AI, MLOps and capstone projects.
Topics: Computer architecture, operating systems, file systems, binary, software lifecycle. Tools: Windows/Linux, VS Code.
Topics: Algorithms, flowcharts, pseudocode, decomposition. Tools: Flowgorithm, Python.
Topics: Variables, operators, control flow, loops, functions. Tools: Python.
Topics: Classes, objects, inheritance, polymorphism, encapsulation. Tools: Python.
Topics: Version control, branching, collaboration. Tools: Git, GitHub.
Topics: Data lifecycle, CRISP-DM, business understanding. Tools: Jupyter Notebook.
Topics: Structured/unstructured data, APIs, CSV, JSON. Tools: Pandas, Requests.
Topics: Database connections, SQL integration. Tools: PostgreSQL.
Topics: ETL, joins, data merging. Tools: Pandas.
Topics: Validation rules, integrity, consistency. Tools: Pandas.
Topics: Data quality dimensions, profiling. Tools: Pandas.
Topics: Missing data strategies, duplicate handling. Tools: Pandas.
Topics: IQR, Z-score, anomaly detection. Tools: Pandas, NumPy.
Topics: Encoding, scaling, feature extraction. Tools: Scikit-learn.
Topics: Normalization, standardization. Tools: Scikit-learn.
Topics: Mean, median, variance, distributions. Tools: NumPy.
Topics: Correlation, distributions, trends. Tools: Pandas, Seaborn.
Topics: Hypothesis testing, confidence intervals. Tools: SciPy.
Topics: Trends, seasonality, anomalies. Tools: Plotly.
Topics: Storytelling, KPIs. Tools: Power BI.
Topics: SELECT, WHERE, ORDER BY. Tools: PostgreSQL.
Topics: JOIN, GROUP BY, HAVING. Tools: PostgreSQL.
Topics: Ranking, partitions. Tools: PostgreSQL.
Topics: Indexes, execution plans. Tools: PostgreSQL.
Topics: ER diagrams, normalization. Tools: PostgreSQL.
Topics: Chart selection, perception. Tools: Matplotlib.
Topics: Histograms, boxplots, scatter plots. Tools: Seaborn.
Topics: Dashboard design. Tools: Plotly.
Topics: BI reporting, KPIs. Tools: Power BI.
Topics: Dashboard publishing. Tools: Tableau.
Topics: Supervised & unsupervised learning. Tools: Scikit-learn.
Topics: Linear, polynomial regression. Tools: Scikit-learn.
Topics: Logistic regression, trees, SVM. Tools: Scikit-learn.
Topics: K-Means, DBSCAN. Tools: Scikit-learn.
Topics: Metrics, cross-validation. Tools: Scikit-learn.
Topics: Perceptrons, backpropagation. Tools: PyTorch.
Topics: Convolution, pooling. Tools: PyTorch.
Topics: Fine-tuning. Tools: PyTorch.
Topics: Optimizers, regularization. Tools: PyTorch.
Topics: Image processing. Tools: OpenCV.
Topics: Tokenization, cleaning. Tools: spaCy.
Topics: Embeddings, sentiment analysis. Tools: Hugging Face.
Topics: Attention, transformers. Tools: Hugging Face.
Topics: Embeddings, vector databases, RAG. Tools: ChromaDB, LangChain.
Topics: Prompt design, function calling, AI agents. Tools: LangChain, Ollama.
Topics: REST APIs. Tools: FastAPI.
Topics: Containers. Tools: Docker.
Topics: ML lifecycle. Tools: MLflow.
Topics: CI/CD pipelines. Tools: GitHub Actions.
Topics: Drift detection, monitoring. Tools: MLflow.
Topics: Requirements analysis. Tools: All tools.
Topics: ETL, preprocessing. Tools: All tools.
Topics: ML & DL integration. Tools: All tools.
Topics: APIs, Docker. Tools: FastAPI, Docker.
Topics: Technical documentation, communication. Tools: GitHub, Markdown.
Apply your knowledge through guided exercises and project-style applications. Specific tools, projects and assessment arrangements should be confirmed with the admissions team.
Prepare and explore real-world datasets with Python, statistics and visualisations.
Train classification or regression models and evaluate predictions using suitable metrics.
Explore text processing, transformers and retrieval-augmented generation workflows.
Develop, containerise, deploy and present an AI or data science project.
The approved programme syllabus states a minimum educational qualification of 12th grade pass. Confirm current admission terms with the institute.
Professional Diploma in AI & Data Science.
Ask admissions about current classroom or online study options, project mentoring and upcoming batches.
The Insta Infotech course listing refers to Medhavi Skills University and academic credits. Confirm the university-award arrangements, credit conditions and official documentation before admission.
These are illustrative career pathways related to the skills covered. Eligibility for individual roles depends on employer requirements, qualifications and experience; employment is not guaranteed.
Prepare datasets, visualise trends and create useful reports.
Build dashboards and track business performance metrics.
Support model training, testing and evaluation under guidance.
Support data preparation, statistical analysis and predictive modelling.
Develop scripts, data workflows and service integrations using Python.
Support AI features, APIs and model-based applications.
The curriculum includes Python, data gathering and cleaning, statistics, SQL, data visualisation, machine learning, neural networks, NLP, transformers, Generative AI, APIs, containerisation, monitoring and capstone work.
Yes. The curriculum includes transformers and large language models, retrieval-augmented generation, vector search, prompt engineering and AI agents.
The curriculum includes practical labs, mini projects and end-to-end project development. Ask admissions for current lab access and assessment requirements.
The syllabus starts with computing fundamentals, computational thinking and Python programming. The stated minimum qualification is 12th grade pass; confirm other admission requirements with Insta Infotech.
Yes. Modules cover regression, classification, clustering, neural networks, CNNs, transfer learning and model evaluation.
Ask Insta Infotech to confirm the exact issuing institution, academic-credit entitlement and applicable conditions in writing.
No. Career examples are illustrative. Ask admissions what current career support is offered; job placement is not guaranteed.
Contact Insta Infotech for current fees, batch availability, learning mode, training centre and enrollment information.
Request the detailed curriculum, eligibility criteria, fees, academic award information and next batch details from Insta Infotech.
Request Course Details
Earn industry-relevant Certificates and Diplomas awarded by Medhavi Skills University, a UGC-recognized University. Insta Infotech is Approved Training Partner of Medhavi Skills University, ensuring quality education and credible certification.
All Certificates and Diplomas are digitally verifiable through Government of India platforms, including Skill India Digital Hub (MSDE), ABC.gov.in (Ministry of Education), and DigiLocker, ensuring authenticity and nationwide recognition.
Our courses are aligned with the National Credit Framework (NCrF) under the National Education Policy (NEP) 2020. Learners earn academic credits that strengthen their skill-based education profile and can be seamlessly transferred toward higher education pathways.
NCrF-aligned skill credits are recognized across the UK, EU, and Australian education systems. Through MSU’s global partnerships, learners benefit from dual certification opportunities and accelerated pathways to international degree programs.
Insta Infotech empowers learners with future-ready skills. Backed by the Skill India Mission and our academic partnership with Medhavi Skills University, we bridge the gap between education and employment through practical, hands-on learning and nationally recognized certifications.
Quality Skill Education — this is not merely a certificate of attendance, but a verified academic credential that enhances credibility and opens opportunities across MNCs, embassies, and government sectors.
Our programs are certified by a recognized university, ensuring legal authenticity, academic validity, and strong professional acceptance. This means your qualification carries real value for employment, career advancement, and higher education.
Our programs combine practical training, real-world projects, and industry-relevant skills to prepare students for immediate employment. we ensure learners confidently transition from education to professional careers.
Our programs follow internationally aligned curricula and current industry requirements, ensuring learners gain globally relevant knowledge, practical competencies, and professional practices. This prepares students to adapt, compete, and work confidently.
Aligned with the Skill India Mission, we transform vocational training into a nationally recognized qualification, enabling our students to become part of India’s formal skilled workforce.
Through the National Credit Framework (NCrF), our courses are not merely extra-curricular; they are credit-earning modules that contribute directly toward your formal higher education pathway.
Aligned with the National Education Policy 2020, we transform traditional IT education into a multidisciplinary, skilled-based vocational pathway that enables students to earn formal academic credits.
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