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Job Ready PG Diploma in Data Science and AI

In Collaboration with Shivaji University, Kolhapur

Job-ready PG Diploma in Data Science and AI is a 6-month comprehensive program designed in collaboration with Shivaji University, Kolhapur, to bring out a practical approach in learning. Jumpstart the Career with hands-on exposure to key technologies including Python programming, Machine learning, natural language processing, deep learning, Deployment on AWS, and 20+ industry projects.

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3 MONTH REAL-TIME INTERNSHIP

100+ Hrs of live sessions

Weekly Doubt Clearing Sessions

1:1 Mentorship

A 3 MONTH REAL-TIME INTERNSHIP

The program aims at helping learners develop a robust skillset that will culminate into an opportunity to work on real-time projects with our industry partners.

Key Course Highlights

100+ Hrs of live sessions

Weekly live workshop with Industry Experts

Dedicated Career Services

1:1 Mentorship

Doubt-Clearing Sessions, Daily quizzes & assignments,

Most Comprehensive Syllabus in the Industry

Lifetime access to content

20+ Industry Projects & Case Studies

24*7 Support

Low-cost course in the Market

Learn from real-life Data Scientists & Industry Practitioners

Both for Working Professionals & Fresher's

Guaranteed 3 Interviews

No Cost EMI Option

Top Skills You Will Learn

Statistics

Python

Machine Learning

Data Visualization

Deep Learning

Natural Language Processing

Model Deployment

Corporate Communication

Program Highlights

Cumulative Period-6 months

3 months paid Internship

Total hours of Course Delivery-100+ hours

20+ Industry Projects & Case studies

Personalized feedback

No Programming Knowledge Required

About VisionNLP

Vision NLP was founded with a vision to train next-gen Data Science engineers. We provide an immersive and real-world learning experience for freshers and professionals looking for a transition. Our courses include Data visualization, Data processing, Predictive modeling, Artificial Intelligence, Machine learning, NLP, end-to-end model deployment. We assist students in landing that perfect job by building their portfolio with projects, mock interviews and assignments. Our mentors are real-world data scientists that help them master the domain knowledge required to excel.

Why should you choose a data science career?

We live in the 'data era'. Business, accounting, education, science, engineering, healthcare is data-driven. Working with data gives you the right edge

Up-and-coming field

Data science can get you gigs for side income

An opportunity to offer a transition

“According to recruitment firm Michael Page's 2021 India Talent Trends report, data science professionals with

3-10 years of experience can get a package of 25-65 lakh range

More than 10+ years experience have packages upwards of 1 crore.

With over 15 years of experience can get paid up to 1.8 crores.

Average annual pay hike for data science professionals falls between 20-30% compared with 15-20% for professionals from other backgrounds.”

-India Today

"Data Science jobs are one of the best career options in 2021 in India."

-Analytics Insight

"Data science needs will create roughly 11.5 million job openings by 2026."

-BLS, Bureau of labour statistics, U.S. Department of Labour

Start your journey in Data Science today!

Who should apply?

This data science program is specially designed to prepare students in these broad disciplines to gain practical know-how and the proper methodologies.

You get the right plan and guidance for the new start or transition.

Anyone can enroll

Without coding background

Even Fresh graduates

Professionals looking for career transition

Top Career to choose from

Data Scientist

Data Analyst

Data Engineers

Data Architect

Data and Analytics Manager

Business Intelligence Developer

Machine Learning Engineer

Business Analyst

Database Administrator

And more

Meet the Faculty


Shweta Gargade

Shweta Gargade is an exceptional Data Scientist. She has worked in various product and service based companies for 4.5+ years; she specializes in research and development of Speech Synthesis, Speech Recognition, Voice Cloning, and NLP. She is a top-rated Upwork freelancer in this upcoming field with a 100% job score.

Shridhar Pawar

Sridhar is an NLP Data scientist with Indium and has extensively worked on face recognition, Video processing, Speech recognition). His core philosophy is "Learn, Create and Explore." A multidisciplinary professional with a degree in Masters in Applied Statistics from Kolhapur University, Sridhar has experience in Statistics, Predictive Analytics, Machine learning, Deep learning, Image processing, AI, NLP, Python, Tensorflow, PyTorch SQL and R.

Somnath Pawar

Somnath Pawar is an Assistant professor with Shivaji University and leads the team by aligning students' interests with University needs. He trains students in real-world data steps in the data science lifecycle: defining the problem at hand to be solved, gathering, cleaning, visualizing the data, feature engineering, training and deploying a variety of machine learning models and quantifying the business impact.

Testimonials

After talking to my friend, I enrolled in this course, and I decided to go for this one because of the curriculum and the feel of it during the assessment process. Shweta mam knew what she was doing. They provided complete profile building, interviews and a great internship opportunity with valuable feedback on the areas I needed to improve—gratitude to Ma'am and her team.

Srilekha, B.COM Graduate

I joined VisionNLP Academy a few months back to help me make a career transition from Sales into Data Science, and in 3 months, it worked! I increased my salary, quickly making it worth my time. It was a purely financial decision, and I am now working in a new exciting field. I chose them over others because I was impressed with their instructors, and they offer continuous career support after graduating.

Ashwin, Sales Manager, MNC

I never imagined something as serious as machine learning could be taught with such ease in an online live session. Everything about your course is unique, from your lectures to the development environment and the recommendations and links. I loved your feedback. So helpful.

Prasad Aggarwal, BSc. Final

Just brilliant, I don’t have words to express how confident I am feeling with this new start. I was confused about where to start as I was stuck in my career. I met Shweta Mam and could apply everything in my work. I could learn how to code and also the 'why' behind it. I would recommend this course to anyone who is looking for a new beginning.

Shiv Shakti, FMCG Business Head

Hands-on Projects

We believe that applying course content to answer questions, solve real-world problems beyond just receiving content can improve learning and increase motivation for learning.

Engage in collaborative projects in a box format - 3X3

20+ Domains, 10+ domains



Real-estate

Data Science in Real Estate helps identify and manage risks, forecast customer behavior and increase engagement. It offers more personalized solutions to clients while automating processes to boost employee performance.

Transportation and Logistics

Data Science can automate insights, alerts, reports and data exchange more quickly for the transport industry. Reducing freight costs by optimizing the delivery path and extending the life of assets through finding patterns in usage data.

Healthcare analytics

Data science can help hospitals take preventive steps as it can predict the deterioration in patients' health and recommend patients start an early treatment that will assist in reducing the risk of the further aggravation of patient health.

Automobile analytics

Data science helps improve everything from research to design and manufacturing to marketing processes in the automobile industry.

Pharma

Data Science can reduce the cost and speed up clinical trials by identifying and analyzing various data points for the participants.

Banking/Finance

Data Science has far-fetched effects in the Banking and Financial service sector as the insights accumulated help draw a pattern of customer behaviors. These patterns can lead to personalized interactions with each customer and generate new revenue generation strategies accordingly.

Education

Data Science empowers educators to perform data visualization, data reduction and description, and prediction tasks and inform policymakers and stakeholders, leading to correct measures and policies.

E-commerce

Data Science can affect purchases, profits, losses and even manipulate customer behavior. Even stakeholders can derive valuable insights from a large number of online customer reviews and ratings.

Others

The list is big and each of them are exciting in it's own way. There is no limitation to where data science can be applied. This is just the tip of the iceberge and the show is yet to begin.

Career Center


Placement assistance

3 guaranteed interviews: We handhold you after the program and provide a chance to be screened and evaluated by prospective employers in 3 interviews.

Access to 100+ job postings: We have a community of Data Scientist in which you can get alerted about 100+ job postings.


Interview preparation

Mock interview: Our state-of-the-art placement cell prepare you for interview through mock interviews

1:1 mentorship: You get access to one-on-one mentorship opportunities with real world Data Scientists that can help you take a deep-dive into this stream.


Build profile

Career-oriented session: Our weekly sessions are designed to increase your awareness of career related trends and happenings.

Resume & LinkedIn profile building: Our experts will work with you to create excellent profiles that can help you gain attention of the talent acquisition staff of major organizations.

Github & Hackerank: We help you share your projects on the most used platforms to make you an expert in your chosen language.

Kaggle: We help you access free GPUs and a huge repository of community published data & code in the Kaggle community.

Syllabus

  • Welcome to the program
  • What is Data Science
  • Application of Data science
  • Learning path of Data Science

  • Introduction to Python
  • Why Python for Data Science
  • Introduction to various Operating systems
  • Python Installation and Python IDE’s
    • How to run for different OS (Windows, Linux)
    • Spyder, Jupyter Notebook, Google Collab
    • Editor - Sublime Text, Atom, VSC
  • Basics of python for data science
    • Arithmetic operators
    • Variables and assignment operators
    • Data Types
    • Data Structures of python
  • Loops and conditions
    • for, while, Nested loop
    • if, else, elif, nested if
    • break, continue, pass
  • Object Oriented Programming
    • functions
    • Classes and Object
    • Inheritance
  • Numpy (Numerical Python)
  • Pandas
  • Regular Expressions

  • Data understanding
  • Missing value techniques
  • Outlier detection and treatment
  • Subset selection
    • Autocorrelation and Multicollinearity
    • Variance Inflation Factor (VIF)
  • Dummy variable Implementation
    • Encoding methods on nominal variables
    • Deriving new variables from numerical variables
  • Data Visualizations
    • Histogram
    • Barplot, Boxplot
    • Correlation heat map

  • Need of Statistics and Mathematics
  • Introduction to Probability
  • Random variables
  • Discrete probability distributions
  • Continuous probability distributions
  • Confidence Interval and its importance
  • Central limit theorem
  • Sampling Techniques
  • P-value
  • Hypothesis testing
  • Anova
  • Correlation
  • Ordinary Least square methods
  • Multiple Linear regression
  • Advanced regression techniques
  • R^2 value and Adjusted R^2 value

  • All about machine learning
  • Matrices
    • RMSE, Confusion Matrix
    • Accuracy and Misclassification error
    • Sensitivity and Specificity
    • Precision and Recall, F1-score
    • ROC-AUC curve
    • Cohen's kappa, Lift and Gain
  • Model improvement
    • Overfitting, Bias-variance tradeoff
    • Imbalanced Dataset problem
    • L1 and l2 regularization
    • Hyperparameter tuning
  • Logistic Regression
    • Concepts of MLE
    • Drawbacks of Linear Regression fails
    • Sigmoid function, log odds ratio
    • Cost Function
  • k-Nearest Neighbors
    • What is KNN?
    • Elbow Method
    • KNN detailed algorithm
  • Naive Bayes
    • Bayes theorem
  • Decision Tree and Random Forest
    • Construction of tree
    • terminologies
    • Gini index
    • information gain
    • optimizing performance
    • variable importance
  • Support Vector Machines (SVM)
    • Rewind of basic calculus
    • Decision Boundary
    • Hyperplane
    • LaGrange’s Theorem
    • Hinge loss
  • Bagging & Boosting
    • Bagging
    • XgBoost
    • AdaBoost

  • Introduction to Unsupervised Learning
  • Distance Metrics
  • Clustering and its types
    • Hierarchical Clustering
    • K-means Clustering
    • Density-Based Clustering
  • Dimensionality Reduction
    • Principal Component Analysis

  • Understanding Time Series Data
  • Visualizing and Understanding Time Series Components
  • Autocovariance
  • ACF and PACF
  • Autoregressive models: AR, MA, ARMA, ARIMA
  • Exponential Smoothing
  • Holt-Winters Model

  • Introduction to NLP
  • NLTK, regex, spacy, string processing
  • Data Preparation
    • punctuation removal
    • stop-words removal
    • numeric value removal
    • frequent words removal
    • rare words removal
    • spelling correction
    • tokenization, stemming, lemmatization.
  • Part of Speech
  • Named Entity Recognition
  • Feature Engineering: count vectors as features
  • Term Frequency-Inverse Document Frequency (TF-IDF)
  • word embeddings, word2vec
  • Similarity score - Cosine similarity

  • Introduction to Artificial Neural Network
  • Biological and Artificial Neurons
  • Activation Functions
    • Rectified Linear Activation (ReLU)
    • Sigmoid
    • Hyperbolic tangent (tanH)
    • Softmax
  • Types of neural network
    • Perceptron
    • Feed Forward Network
    • Multi-Layer Perceptron (MLP)
    • Back Propagation
    • Deep ANN
    • Transfer Learning

  • GPU Introduction
  • Various type of GPU configuration
  • GPU provider and its pricing
  • Paperspace or AWS GPU setup
  • Running model in GPU
  • Flask API
  • Swagger and Postman

Frequently Asked Questions

Yes, you can join the Data Science Program. All the essential programming we can teach you during the tenure of this course.

Yes, why not as long as you can do thorough research. You will learn and arrive naturally at the essential statistics skills.

We help you get three guaranteed interviews, and you are also added to the data science communities on various platforms where we keep on informing you about the latest job openings.

We have a community of data scientists where you can connect and solve all your problems and concerns.



Fee Structure

Best-in-class content by leading faculty and industry leaders in the form of live online sessions, cases and projects, assignments and live sessions

  • Total - 19,999/-
  • No cost EMI - 6,700/-
  • Registration Fee 1000 (non-refundable)

Hurry It's Limited!

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