Welcome To Best Python Data Science Course Institute In Guntur
Job Opportunities After Completing Machine Learning Python Course in Guntur
Machine Learning with Python is a simple, secure, and easy to learn programming language when compared to other programming languages. Huge demand for Machine Learning developers & professionals assures more career opportunities because there has rapid growth for self-driving cars, Amazon Alexa, Catboats, recommender systems, and many more which choose Machine Learning as the preferred programming language. Top-rated companies like Facebook, Pinterest, Instagram, Disqus, and other organizations including NASA use Machine Learning for making various predictions, including weather forecasting, stock market analysis, disease prediction, etc.
If you are looking for better job opportunities as a developer, get training in Machine Learning with Python. Because in the current future, machine learning has made great progress in its research, and it is now everywhere around us. Especially machine learning, helps in fetching up a career with various job opportunities.
Data Science Specialist
Machine Learning Specialist
Data Science Consultant
Why Choose Nipuna Technologies for Machine Learning Python Course in Guntur ?
Our Machine learning with Python training program has been designed by expert trainers for students to get the maximum in-depth knowledge with the support of our highly-skilled training team. This Machine learning courses is totally placement-oriented with more prominence given to real-time exposure. Nipuna Technologies is the best Machine learning with Python Training Institutes in Guntur offers job-oriented and placement Focused classrooms & Online Machine learning with Python course in Guntur. We provide A/C Class Rooms, High Configured Lab & well Experienced Trainers. We also offer students the best Machine learning with Python training classes with real-time applications by the expert trainers in Guntur. The Machine learning with Python Training program at Nipuna technologies is specially designed for both Graduates and working professionals.
Python Data Science Course Key Features
Practice Labs For Real-Time Learning
Practice Labs makes it easy for you to put your learning into practice in a safe environment that you can access anytime with a compatible PC, Browser and Internet connection.
Live Project Training
We offer Live Projects and opportunity to take part in project design supported by industry partners including business and community organizations.
We will use collaborative web conferencing with screen sharing to conduct highly interactive live online teaching sessions.
Got queries? Our 24/7 support team will go extra mile so you can have easy and enjoyable experience with Nipuna Technologies on Slack which is a communication platform.
Job & Interview Assistance
Our interview assistance can help you overcome your fears and walk into your next interview with confidence and get your dream Job.
Internship After Course
Industry needs the best talent to stay afloat and thrive in today’s fast and ever-changing world, you will get a chance to do Internships and working closely that can provide a serious winwin for both Industry and students/trainees
Python Data Science Course Curriculum
List of all the topics which will be covered in Python Data Science Course
- About Applications of Machine Learning
- About Supervised Vs Unsupervised Learning
- About the Overall process of executing the ML project
- About Stages of ML Project
- About Concept of Overfitting and Under-fitting (Bias- Variance Trade-off) & Performance Metrics
- About Concept of feature engineering
- About Regularization (LASSO, Elastic net, and Ridge)
- About Types of Cross-validation (Train & Test, K-Fold validation, etc.)
- About Concept of optimization – Gradient descent algorithm
- About Cost & optimization functions
- About Python libraries suitable for Machine Learning
- About Principle Component Analysis
- About K-Means Clustering
- About Hierarchical Clustering
- About Density-Based Clustering
- About Content-based recommender systems
- About Collaborative Filtering
- Time Series Forecasting
- About What is forecasting?
- About Applications of forecasting
- About Time Series Components and Decomposition
- About Types of Seasonality
- About Important terminology: lag, lead, Stationary, stationary tests, autocorrelation & white noise, ACF & PACF plots, auto-regression, differencing
- About Classification of Time Series Techniques (Univariate & Multivariate)
- About Time Series Modeling & Forecasting Techniques
- About Averages (Moving average, Weighted Moving Average)
- About ETS models (Holt Winter Methods)
- About Seasonal Decomposition
- About ARIMA/ARIMAX/SARIMA/SARIMAX
- About Regression
- About Evaluation of Forecasting Models
- Introduction to Text Mining
- About Text Mining – characteristics, trends
- About Text, Processing using Base Python & Pandas, Regular Expressions
- About Text processing using string functions & methods
- About Understanding regular expressions
- About Identifying patterns in the text using regular expressions
- About Getting Started with NLTK
- About Introduction to NLP & NLTK
- About Introduction to NLTK Modules (corpus, tokenize, Stem, collocations, tag, classify, cluster, tbl, chunk, Parse, ccg, sem, inference, metrics, app, chat, toolbox, etc.)
- About Vectorization (Count, TF-IDF, Word Embedding)
- About Sentiment analysis (vocabulary approach, based on Bayesian probability methods)
- About Name entity recognition (NER)
- About Methods of data visualization
- About word length counts plot
- About word frequency plots
- About word clouds
- About correlation plots
- About letter frequency plot
- About Heat map
- About Grouping texts using different methods
- About Language Models and n-grams — Statistical Models of Unseen Data (Smoothing)
- About Semantic similarity between texts
- About Text Segmentation
- About Topic Mining (LDA)
- About Text Classification (spam detection, sentiment analysis, Intent Analysis)
- About Reading data from file folder/from text file, from the Internet & Web scrapping, Data Parsing
- About Cleaning and normalization of data
- About Sentence Tokenize and Word Tokenize, Removing insignificant words(“stop words”), Removing special symbols, removing bullet points and digits, changing letters to lowercase, stemming /lemmatization/chunking.
- About Creating Term-Document matrix
- About Tagging text with parts of speech
- About Word Sense Disambiguation
- About Finding associations
- About Measurement of similarity between documents and terms
- About Visualization of term significance in the form of word clouds
Our training is based on latest cutting-edge infrastructure technology which makes you ready for the industry. Nipuna Technologies will present this certificate to students or employee trainees upon successful completion of the course which will encourage and add to trainee’s resume to explore a lot of opportunities beyond position.