Masters in Data Science and Data Analytics

The exclusive course designed by VisonNLP has been hand crafter by Industry expert to give you complete exposure to all the tools, techniques and industry practices making you an expert in the subject matter and enabling to jump a leap ahead of others. This course covers Python, Data Science, Data Analysis, Data visualization, stats, Maths, AI, Machine Learning,Prediction algorithms, SQL, and Database equiping you with all that you need.

Key Course Highlights

1:1 Mentorship

Doubt Clearing Session

100+ hours Course

Real-world projects

Top Skills You Will Learn

Python

Data Science

Data Analysis,

Data visualization

Stats

Maths

Artificial Intelligence (AI)

Machine Learning

Prediction algorithms

SQL

Database

Meet your Tech Warrior

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.

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

Syllabus

What is Data Science
Applications of Data science
Learning path to become a Data Scientist

Introduction to Python
Introduction to various Operating systems
Python Installation on Different OS
Python IDE’s and Python Editors
Jupyter Notebook and Basics of Python
Python Operators, Variables
Data Types
Data Structures
Loops in Python
Conditional statements
Object Oriented Programming
Pandas
Numpy

Need of Statistics and Mathematics
Probability
Random variables
Discrete probability distributions
Continuous probability distributions
Sampling Techniques
P-value
Hypothesis testing
ANOVA
Correlation
Linear Algebra
Calculus – Derivatives and Functions

Data understanding
Missing value techniques
Outlier detection and treatment
Multi-collinearity
Deal with Categorical data
Feature Engineering
Feature selection
Feature Scaling and Standardization

Histogram
Bar plot, Boxplot
Correlation heat map
Scatter plot
Set Axis, Labels, and Legend Properties

Introduction to Machine learning
Model Evaluation Matrices RMSE, Confusion Matrix, Accuracy, Misclassification error, Sensitivity and Specificity, Precision and Recall, F1-score, ROC-AUC curve, Cohen's kappa
Linear regression Simple Linear regression, Multiple Linear regression, OLS, Advanced regression techniques, R^2 value and Adjusted R^2 value
Cost Function and Gradient Descent
Logistic Regression Drawbacks of Linear Regression fails, Concepts of MLE, Sigmoid function, log odds ratio
K-Nearest Neighbour’s, Naive Bayes What is KNN, Elbow Method, KNN detailed algorithm, Bayes theorem
Support Vector Machines (SVM) Rewind of basic calculus, Decision Boundary, Hyperplane, LaGrange’s Theorem
Decision Tree and Random Forest Construction of tree, terminologies, Gini index, information gain, optimizing performance, variable importance
Ensemble Learning: Bagging & Boosting

Overfitting, Bias-variance trade-off
Cross-validation
Imbalanced Dataset
L1 and L2 regularization
Hyperparameter tuningion to Python

Introduction to Unsupervised Learning
Distance Metrics
Clustering: K-means Clustering
Principal Component Analysis

SQL, DBMS and SQL Server Detailed Understanding
SQL Server Services & Tools
SQL Queries Clauses
Data Manipulation
Operators & in-built functions
Create, Alter, Drop, rename, Delete, Insert
SQL joins
Bonus points & Many more

Introduction to Tableau
Data Visualization in Tableau

Masters in Data Science and Data Analytics