Industry Readiness Program

450 hours of training in final year of UG program OR .

2 Value Add courses per semester of UG program.

Learn 6 Foundation modules + 6 Advanced Modules.

Master 10 essential skills for Data analyst roles.

Learn 21 Tools used in Industry.

Batches Starts From





Upskill for your Dream Job

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Our Learners work in top Companies

L&T Infotech
L&T Infotech
L&T Infotech
L&T Infotech
L&T Infotech
L&T Infotech
L&T Infotech
L&T Infotech
L&T Infotech

National & International Credentials


About Industry Readiness Program

India’s National Educational Policy [NEP] places a strong emphasis on multidisciplinary learning. NEP allows educational institutions freedom for integrating diverse perspectives and providing hands-on experiences with new-age tools and ensure that students develop well-rounded skills set that aligns with the evolving demands of the job market.

As industries increasingly rely on Artificial Intelligence [AI] and Machine Learning [ML], individuals equipped with the practical skills gained in these technologies are well-positioned to meet the demands of the modern workplace.

The Industry Readiness program will bridge the gap between education and employability, empowering your students to navigate the digital era with confidence and contribute meaningfully to the workforce of tomorrow.

Objective of the Industry Readiness program

Build a Strong Foundation in Data Science Concepts: Equip participants with a thorough understanding of key data science principles, including statistics, data manipulation, and machine learning. This foundation ensures they can analyze and interpret complex datasets effectively.

Enhance Technical Competency : Equip students with advanced data science skills, covering key areas such as machine learning, statistical analysis, and data visualization. Ensure learners are proficient in using industry-standard tools and software, preparing them for real-world applications and challenges.

Promote Interdisciplinary Learning : Integrate data science with other disciplines to foster a holistic understanding of its applications across various sectors. Encourage collaborative projects and research that combine knowledge from fields like computer science, mathematics, and business.

Support Lifelong Learning and Flexibility : Align with the NEP’s emphasis on flexibility in education, offering modular courses, industry readiness skills and continuous learning opportunities. Enable students to learn at their own pace, with options for reskilling and upskilling throughout their careers.

Facilitate Industry Connections and Employability : Build strong ties with industry partners to provide students with internships, mentorships, and networking opportunities. Focus on employability skills such as communication, teamwork, and project management, ensuring graduates are job-ready and able to integrate smoothly into the workforce.

Improve Soft Skills and Professional Readiness: Include training in communication, teamwork, and professional ethics to prepare participants for corporate environments. These skills are essential for effective collaboration and career advancement.

Provide Career Support and Networking Opportunities: Offer services like resume building, interview preparation, and networking events with industry professionals. These resources help participants transition smoothly into the workforce and connect with potential employers.

How our program works

Option-1 : Online + self-paced. Masterclasses are delivered by distinguished faculty from Bhrighu

Option-2 : Hybrid model which includes Face-2-Face in class teaching, Online + self-paced.

25+ hands-on mini-projects picked up from multiple industries

Capstone projects in 3 domains.

Option-1 : Learner gets NASSCOM FSP Certificate

Option-2 : Learner gets IEEE, USA Certificate

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Why Join Industry Readiness program

Career Development Support

Career Development Support

We are committed to not only educating but also ensuring the career success of our participants. For Educational Institutions who choose to partner with Bhrighu, the program includes extensive career development support, such as resume building, interview preparation, and networking opportunities with industry professionals. Our career services team will work closely with participants to tailor their job search strategy and connect them with potential employers. We offer internships and live industry projects to provide hands-on experience and facilitate real-world learning. Additionally, our strong industry partnerships often lead to direct recruitment opportunities for those who complete this program. To further ensure your confidence in our program, we guarantee a full refund if you do not secure a job within 10 months of completion. This comprehensive career support framework is designed to maximize employment prospects and career growth.

Hands-On Learning

Hands-On Learning

Our program emphasizes practical, hands-on learning through numerous real-world projects and exercises. Participants engage in projects that mimic actual industry scenarios, enabling them to apply theoretical concepts in a practical setting. This experiential learning approach fosters critical problem-solving skills and allows students to build a robust portfolio of work. Capstone projects, often developed in collaboration with industry partners, provide invaluable exposure to real-world challenges and enhance employability. This practical focus ensures that participants who complete the program are not just knowledgeable, but also experienced and job-ready.

Flexible Learning Options

Flexible Learning Options

Understanding the varied schedules and commitments of our participants, we offer a self-paced online learning option to accommodate everyone. Our program allows you to learn at your own convenience, from any place, and on any device, ensuring that education fits seamlessly into your busy life. This flexibility ensures that more people can access our top-tier training and benefit from the program at their own pace. Our robust online learning platform provides a seamless and interactive educational experience, complete with recorded lectures, interactive modules, and a wealth of resources accessible anytime. This adaptability makes it easier for participants to balance their learning with personal and professional responsibilities, offering the ultimate convenience in education.

Comprehensive Curriculum

Comprehensive Curriculum

The Industry Readiness Program offers a meticulously crafted curriculum that covers both foundation as well as advanced aspects of data science, ensuring a holistic learning experience. Participants gain a deep understanding of statistics, machine learning, deep learning, and big data technologies, among others. This comprehensive approach prepares students not only to understand but to master the essential tools and techniques required in the industry. Our program is continually updated to reflect the latest advancements and industry trends, ensuring relevance and cutting-edge knowledge. By the end of the program, graduates are equipped to tackle a wide range of data-driven challenges.

Expert Faculty and Mentorship

Expert Faculty and Mentorship

The Industry Readiness Program boasts a team of experienced instructors and industry experts who provide top-tier education and mentorship. Our faculty members bring years of professional and academic experience, offering insights that bridge the gap between theory and practice. Personalized mentorship helps guide participants through complex topics and projects, ensuring a deep and thorough understanding. Regular guest lectures and workshops from industry leaders keep students abreast of the latest trends and innovations. This high level of instruction and support is critical to developing proficient and confident data scientists.

What Topics Will Be Covered During The Training


Instructed lead classes

  • Introduction to vectors and matrices, their properties, and operations.

    Techniques like Singular Value Decomposition (SVD) and Eigenvalue decomposition.

    Understanding linear mappings and their applications in data science.

    Importance in Principal Component Analysis (PCA) and other dimensionality reduction techniques.

  • Measures of central tendency, dispersion, and shape of data distributions.

    Basic concepts of probability, conditional probability, and Bayes’ theorem.

    Hypothesis testing, confidence intervals, and p-values.

    Linear regression, multiple regression, and assumptions of regression models.

  • Techniques like linear regression, logistic regression, and support vector machines.

    Clustering methods like K-means and hierarchical clustering.

    Metrics like accuracy, precision, recall, F1 score, and ROC-AUC.

    Techniques for selecting, creating, and transforming features to improve model performance.

  • Basics of neural networks, activation functions, and architectures.

    Layers, operations, and applications in image processing.

    Architectures, applications in sequence data, and LSTMs/GRUs.

    Optimization techniques, loss functions, and regularization methods.

  • Syntax, data types, control structures, and functions.

    Using libraries like NumPy and pandas for data analysis and manipulation.

    Creating plots and charts using Matplotlib and Seaborn.

    Leveraging SciPy for scientific and technical computing tasks.

  • Syntax, data structures, and basic programming constructs.

    Using DPLYR and TIDYR for data wrangling and cleaning.

    Performing statistical tests and building regression models.

    Creating graphs and plots using GGPLOT2.

  • History, types, and applications of AI.

    Techniques like A*, minimax, and genetic algorithms.

    Rule-based systems and their applications in AI.

    Ethical considerations and societal impacts of AI technologies.

  • Basic concepts, architecture, and setting up the environment.

    Creating neural network models using Keras high-level API.

    Techniques for training models, monitoring performance, and tuning hyperparameters.

    Exporting and deploying models for production use.

  • Iterative development, quick proof of concepts, and agile methodologies.

    Tools and methods for creating visual representations of projects.

    User testing and feedback integration for improving prototypes.

    Refining prototypes based on testing and feedback cycles.

  • Techniques for image enhancement, noise reduction, and normalization.

    Identifying and extracting key features from images using algorithms like SIFT and HOG.

    Methods for segmenting images into meaningful parts and classifying objects.

    Techniques like YOLO and Faster R-CNN for detecting objects within images.

  • Building and applying language models for text prediction and generation.

    Identifying and classifying entities in text data.

    Techniques for translating text from one language to another.

    Converting spoken language into text using NLP techniques.

  • Tokenization, stemming, lemmatization, and stop word removal.

    Techniques like TF-IDF and word embeddings.

    Building models for classifying text data into categories.

    Techniques for analyzing the sentiment expressed in text data.

  • Basics of the Tableau interface and key functionalities.

    Connecting to and integrating various data sources.

    Creating different types of charts, graphs, and dashboards.

    Implementing calculations, parameters, and custom visuals for enhanced analytics.

  • Techniques for video enhancement, frame extraction, and normalization.

    Methods for detecting and analyzing motion in video sequences.

    Algorithms for tracking objects across frames, such as Kalman filter and mean-shift.

    Techniques for classifying video content into different categories.

Tools You'll Master

DALL-E 2 : Master the use of DALL-E 2 for generating high-quality, AI-driven images from textual descriptions, leveraging its deep learning capabilities for creative and practical applications.

Keras : Learn to build and train deep learning models using Keras, a user-friendly API that runs on top of TensorFlow, enabling rapid development of neural networks.

Tableau: Gain expertise in Tableau for powerful data visualization and business intelligence, transforming complex data into interactive, easy-to-understand dashboards.

TensorFlow : Develop proficiency in TensorFlow, an open-source platform for machine learning, to build and deploy machine learning models for various applications.

OpenCV : Learn to use OpenCV, a comprehensive library for computer vision, to process and analyze visual data, enabling applications such as image recognition and video analysis.

Midjourney : Explore the capabilities of Midjourney for AI-driven creative projects, including advanced generative art and design applications.

Scikit-learn : Master Scikit-learn for efficient data mining and data analysis, utilizing its extensive machine learning algorithms and tools.

NLTK : Become proficient with the Natural Language Toolkit (NLTK) for processing and analyzing human language data, essential for NLP projects.

Python : Achieve a strong command of Python, the versatile programming language widely used in data science for its simplicity and powerful libraries.

ChatGPT : Learn to leverage ChatGPT for natural language processing and conversational AI applications, enhancing interactions and automating responses.

SciPy : Utilize SciPy for scientific computing and technical computing, employing its modules for optimization, integration, interpolation, and more.

Plotly : Master Plotly for creating interactive, publication-quality graphs and visualizations in Python, essential for data analysis and presentation.

Seaborn : Gain expertise in Seaborn, a Python visualization library based on matplotlib, to create informative and attractive statistical graphics.

Django : Learn to develop robust web applications using Django, a high-level Python web framework that encourages rapid development and clean, pragmatic design.

Pandas : Become proficient in Pandas for data manipulation and analysis, providing powerful data structures like DataFrames for handling structured data.

NumPy : Master NumPy for numerical computing in Python, essential for handling arrays and performing mathematical operations efficiently.

PyTorch : Learn to use PyTorch, an open-source deep learning framework, for building and training neural networks with a dynamic computational graph.

Bard : Explore Google's Bard for conversational AI, generating human-like text responses for various applications in dialogue systems.

Matplotlib : Develop skills in Matplotlib for creating static, animated, and interactive visualizations in Python, essential for data exploration and presentation.

Flask : Learn to use Flask, a lightweight WSGI web application framework in Python, to build simple and scalable web applications quickly and efficiently.

Credentials offered for completing Industry Readiness program

Option 1

Participants will be issued Vouchers to attend NASSCOM FSP proctored assessment tests.

If you clear the Assessments and Tests for the Industry Readiness program you stand to get Certificate issued by NASSCOM FASP which has National recognition..


Option 2

Bhrighu Academy of E-Learning is an approved provider of IEEE Professional Development Hour [PDH] / Continuing Education Units [CEU] certificates.

Learners who complete the Industry Ready Course successfully with 65% of scores in evaluation will be awarded a certificate.

IEEE will be providing Professional Development Hour [PDH] / Continuing Education Units [CEU] credits for this course



Stay Ahead of the Curve

Enhance Student Employability

Increase your Institution’s placement record

Align with National Educational Policy

Standards Enhance your rankings

Confidence and Competence

Other Benefits

Access to Cutting-Edge Tools and Resources

Access to Exclusive Job Boards

Maximize Networking Opportunities

Boost Institutional Image – attract students, faculty, partnerships

IEEE is a globally recognized organization in the field of electrical engineering, computer science, and related disciplines.

A PDH certificate from IEEE carries international recognition, enhancing the professional standing worldwide and demonstrates ones commitment to ongoing learning