DATA SCIENCE
Unlock the potential of data and embark on a transformative journey with our comprehensive
6-month Data Science Training. In this dynamic program, you will gain the skills and knowledge
needed to navigate the complex world of data, extracting meaningful insights that drive
informed
decision-making. Whether you're a seasoned professional or a newcomer to the field, our
training
is designed to equip you with the tools to succeed in the rapidly evolving landscape of data
science.
TRAINING CONTENT
- Python History & Introduction
- Variables and its Rule
- Data Types: Numeric, Sequence, Boolean, Set, Dict
- Operators: Arithmatic, Logical, Assignement, Comparison, Membership, Identity, Bitwise
- Loops in Python: For, While
- Conditional Statements: if, elif, else
- Control Statements: Break, continue, pass
- Arrays
- Functions: Built-in, User-defined, Anonymous and Recursive
- Object-Oriented Programming: Class,Object, Inheritance, Abstraction, Polymorphism, Encapsulation
- GUI
- File Handling
- Regular Expressions
- Exception Handling
- Project
- Framework (Advanced)
- Flask: Introduction, Enviroment creation, installation, Application, Routing, Variable Rules, URL building, HTTP methods
- History and Introduction of Statistics
- Introduction to Basic Terms
- Variables & Random Variables
- Population,Sample,Population Mean,Sample Mean
- Population Distribution, Sample Distribution and Sampling Distribution
- Measure of Central Tendency- Mean, Median ,Mode
- Measure Of Dispersion - Range, Variance, Standard Deviation
- Many different plotting graphs
- Correlation
- Skewness & Kurtosis
- Testing of Hypothesis: Z test, T-test, ANOVA, Chi-square test
- Numpy
- Pandas
- Matplotlib
- Seaborn
- EDA
- History and Introdunction of SQL
- Properties of database and SQL
- Use of databases
- Types of commands in SQL: DDL,DML,DQL,TCL and etc
- DDL commands and implementation
- DML commands and implementation
- DQL command and implementation
- Clauses in SQL and aggregate functions
- Where ,Order by, Distinct, Limit, Group by, having
- SQL joins: Inner and outer joins
- Constraints in SQL: Not null, unique, primary key, foreign key, index, check , default
- Stored Procedures
- Introduction
- Types of ML: Supervised,Unsupervised and Reinforcement ML with algorithms
- Supervised ML Algorithms with Practicals
- Linear Regression (Simple, Multiple)
- Logistic Regression
- K-Nearest Neighbour
- Decision Tree
- Random Forest
- AdaBoost
- Support Vector Machine
- Naive Bayes Classifier
- Gradient Boost
- Extreme Gradient Boost
- Unsupervised Machine Learning with Practicals
- K-Means Clustering
- Principal Component Analysis
- End to End Project
- What is deep learning ? why ? DL vs ML
- Types of neural network ? its application
- History of perceptron
- Why perceptron failed?
- Neural network basis ,neuron, layer, activation function
- How to build? What are weight and bias?
- Forward and backard propagation ? chain rule?
- Gradient descent
- Stochastic gd , mini batch
- Adadelta, adagrad, rmsprop
- Adam optimizer
- Activation functions sigmoid,tanh,relu,leaky relu,softmax,p-relu,softplus
- Sigmoid vanishing gradient problem
- Relu dying problem
- Exploding gradient
- Advantages , disadvantages and applications
- Loss functions (Mse, mae, huber loss, log error)
- Drop out ratio
- Overfitting problem
- ANN implementation
- CNN architecture, pixel, RGB concept, image structure
- Convolution layer
- Data augmentation, convolution, stride, padding and types, pooling and types
- Edge detection
- CNN implementation
- End to End Project
- NLP introduction
- Basic terminology of Nlp
- NLP pipeline
- Eda - ngram , Wordcloud
- Keyphrase extraction algorithms YAKE RAKE pagerank
- Preprocessing:
- Tokenization - word tokenization, sentence tokenization , whitespace tokenizer, regex tokenization
- Normalization
- Stopwords removal
- Autocorrection
- Language detection and translation with textblob, Google trans
- Stemming, lemmatization
Contact Us
+91-7077070030
info@radiantitservices.inhr@radiantitservices.in
BENEFITS OF THE TRAINING
- Rapid Skill Acquisition
- Hands-On Projects
- Industry-Relevant Curriculum
- Expert Instruction
TRAINING DETAILS
Discover the power of data with our 6-month Data Science Training! This program helps you understand data better so you can make smart decisions . Whether you're new or experienced, our training gives you the skills to succeed in the changing world of data science. Join us and learn to find important information from data!
KEY FEATURE
96 hours of high-quality training contents
Live Project
Experienced Faculty
Placement Support | Post training support
Best Quality Training
In-depth Training Contents
TRAINING DURATION
Our intensive 6-month program is crafted to provide a deep dive into the core concepts of data science while ensuring a time-efficient and immersive learning experience. This condensed timeline allows you to quickly acquire in-demand skills and apply them to real- world scenarios.
REVIEWS
I completed the Data Science training at Radiant IT Services. The instructors taught us important algorithms and statistical models. The hands-on exercises on Python and R programming languages. The tasks related to machine learning models were exceptional. An exceptional training.
Outstanding Data Science training! In-depth coverage of regression, clustering, and cutting-edge techniques like NLP and deep learning. Hands-on experience with Jupyter Notebooks and Pandas. Highly recommended for aspiring data scientists.
Radiant IT Services' Data Science training exceeded expectations. Comprehensive curriculum, practical exercises in TensorFlow and sci-kit-learn, and prompt support for data visualization challenges.
