Data Science with Python
What is Data Science Python? Python is an open-source programming language. That facilitates statistical computing for data preprocessing and graphical libraries for visualization. Being open-source, Python enjoys community support of avid developers who work on releasing new packages, updating Python and making it a steadfast programming package for Data Science.
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Key Features
Skill Level
Beginner, Intermediate, Advance
We are providing Training to the needs from Beginners level to Experts level.
Course Duration
90 Hours
Course will be 90 hrs to 110 hrs duration with real-time projects and covers both teaching and practical sessions.
Total Learners
2000+ Learners
We have already finished 100+ Batches with 100% course completion record.
Assignments Duration
50 Hours
Trainers will provide you the assignments according to your skill sets and needs. Assignment duration will be 50 hrs to 60 hrs.
Support
24 / 7 Support
We are having 24/7 Support team to clear students’ needs and doubts. And special doubt clearing sessions every week.
Our Placement Process
Eligibility Criteria
Placements Training
Interview Q & A
Resume Preparation
Aptitude Test
Mock Interviews
Scheduling Interviews
Job Placement
Batch Schedule
| DATE | COURSE | TRAINING TYPE | BATCH | CITY | REGISTER |
|---|---|---|---|---|---|
| 16/12/2024 | Data Science with Python Course | Classroom / Online | Regular Batch (Mon-Sat) | Pune | Book Now |
| 17/12/2024 | Data Science with Python Course | Classroom / Online | Regular Batch (Mon-Sat) | Pune | Book Now |
| 14/12/2024 | Data Science with Python Course | Classroom / Online | Weekend Batch (Sat-Sun) | Pune | Book Now |
| 14/12/2024 | Data Science with Python Course | Classroom / Online | Weekend Batch (Sat-Sun) | Pune | Book Now |
Data Science with Python Exams & Certification
SevenMentor Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher’s as well as corporate trainees.
Our certification at SevenMentor is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC’s of the world. The certification is only provided after successful completion of our training and practical based projects.
About Data Science with Python
In Python, there is a comprehensive environment that facilitates the performance of statistical operations as well as the generation of data analysis in graphical or text format. The commands that a console takes in as input are assessed and subsequently executed.
At SevenMentor, we are always striving to achieve value for our candidates. We provide Python-Data Science courses which include all recent technologies and tools. Any candidate from any background and having a basic knowledge of computer can enroll for this Data Science with Python Training in Pune. Freshers or experienced candidates can join this course to understand R in analysis and development practically.
We have designed this Data Science with Python Training In Pune to learn Python fundamentals and gently to introduce you to advanced Python concepts also. This Python for Data Science Course in Pune is designed and taught by the experience of working professionals having experience. In SevenMentor we provide the most practical and job oriented training with real-time scenarios. Learn Python in Pune Offered by SevenMentor with Real-time Projects and Data Science Course in Pune with Placement Support. We rated as Best Python-Data Science Training Institute in Pune with Experienced Certified Trainers who have a Knowledge in Python Components like ML, DL, AI, etc.
Batch Schedule for Python-Data Science Training in SevenMentor Pune.
We at SevenMentor understands the need of candidates and preferred batch timings. Currently, we have weekends and weekdays batches for Python training. We also provide flexible batch timings as per demand for Data Science with Python Training In Pune. The total duration for the Best Python-Data science course is 60 Hours. On weekdays batch, training will be of 2 hours each day and at the weekend its 3 hours each day. For more information, the upcoming batches schedule will be updated soon on site. Per batch having a maximum strength of 15 to 20 students.
Why Should I take Python Training?
Python is most widely used by various industries. Now industries are using Python as their primary tool for statistical modeling. The most profound industry that makes use of Python is the Data Science industry and several underlying industries that it comprises of. industries like health, finance, banking, manufacturing and many more.
With Python, you can perform statistical analysis, data analysis as well as machine learning. Python is platform-independent and can be used across multiple operating systems. Python is free owing to its open-source GNU licensing and can be installed by anyone. Python consists of a large collection of graphical libraries. With these libraries, you can make visually appealing and elegant visualizations.
What is Data Science?
Extraction, preparation, analysis, visualization, and maintenance of information is nothing but Data Science. It is a multi-talented field that uses scientific methods and processes to find key-points from data.
"Prompt Engineering for Data Science with Python"
Prompt engineering is a critical aspect of leveraging Python for effective data science tasks, particularly in natural language processing (NLP). It involves crafting precise and targeted instructions or queries to extract meaningful insights from datasets using Python libraries like TensorFlow, PyTorch, or Scikit-learn.
In Python, prompt engineering follows several key principles:
1. Understanding Data: Data scientists must have a deep understanding of the dataset they are working with. This understanding informs the creation of prompts tailored to extract specific information or insights from the data.
2. Leveraging NLP Libraries: Python offers powerful NLP libraries such as NLTK, spaCy, and Gensim. Prompt engineering involves utilizing these libraries to preprocess text data and formulate effective prompts for tasks like text classification, sentiment analysis, and named entity recognition.
3. Model Integration: Python's flexibility allows for seamless integration of prompt-engineered queries with machine learning models. Data scientists can use libraries like TensorFlow and PyTorch to build and train models that generate responses based on the provided prompts.
4. Iterative Development: Prompt engineering often requires an iterative approach. Data scientists experiment with different prompts, evaluate model performance, and refine their approach based on results to achieve optimal outcomes.
5. Documentation and Collaboration: Clear documentation of prompts and their rationale is essential for collaboration and reproducibility. Python's rich ecosystem of tools and frameworks facilitates collaborative development and documentation of prompt engineering processes.
6. Testing and Validation: Rigorous testing and validation of prompts are crucial to ensure they produce reliable and accurate results. Python's testing frameworks like pytest enable data scientists to automate testing procedures and validate prompt-engineered queries efficiently.
Why Should I take Python-Data Science Training?
Data has become the fuel of industries. It is the new electricity. To improve their businesses, Companies require data. To proper decisions making companies deal with the data. Then companies Data Scientists analyze a large set of data to derive meaningful insights. These key points will be helpful for companies to analyze their businesses and their departmental performance in the market. Data Science is used in all areas like commercial industries, healthcare industries, etc. The number of roles for Data Scientists has grown by 75% since 2014. About 14 million jobs will be created by 2025 according to the U.S. Bureau of Labor Statistics. Also, the job of Data Scientist ranks among top emerging jobs on Linkedin. All the statistics point towards the growing demand for Data Scientists.
With the emergence of Python programming in Data Science and data itself, there is a pressing need for efficient Data Science tools that can accommodate the needs of their users. There are also various groups, seminars and boot camps that are being organized around the world that facilitate python education throughout the world. India is one of the biggest producers of data. With many large scale companies and startups searching for ways to convert this massive plethora of data into meaningful insights, there is a need for specialized Data Scientists. In India, Data Scientists who are skilled at Python make on an average of 9 Lacs per annum. Whereas in countries like the USA, they can earn as much as $ 120,000 per annum, on average.
Data is constantly growing at an exponential rate. Therefore, there are bound to be an ample amount of opportunities for aspiring Data Scientists in the future. Many companies are using Python to fulfill their Data Science requirements, therefore, there is a bright future ahead for Data Scientists who are skilled at Python. Available job positions are Data Scientist, Business Analyst, Data Analyst, Data Visualization Expert, Quantitative Analyst.
Why go for best Python-Data Science Training in Pune at SevenMentor?
Here at SevenMentor, we have industry-standard Hadoop curriculum designed by IT professionals. The training we provide is 100% practical. With training, we provide 100+ assignments, POC’s and real-time projects. Additionally CV writing, mock tests, interviews are taken to make candidate industry-ready. We provide detailed notes, interview kit and reference books to every candidate. With the Data Science Course Fees, we develop the students and groom their skills.
Practical assignments at the end of every lecture.
A practical learning experience with a live project.
The individual mock interview session
Real-Time case studies to practice
Job placement assistance with job notification until you get your first job
Course completion certificate
All-time support for your questions.
SevenMentor has a Big Data Science Course in Pune with Placement record since its starting. Every year we create thousands of new job opportunities through various Job Fairs and pool drives across the state.
Data Science for Python Certification in Pune :
Python Certified Data Scientist
Certified Analytics Professional (CAP)
Applied AI with Deep Learning
Cloudera Certified Associate: Data Analyst
Online Classes
SevenMentor’s Online Data Science with Python Training is all you need to launch your career in Data science. Python is the most popular language for data science. There are more than 2.5 million jobs for data science and related professionals. Course syllabus is made with keeping all market standards in mind. In this Online Data Science with Python Course you will understand Python Language basics and how you can apply them in data science. It will make you able to use Python libraries like Pandas and Numpy to analyze data. You can build machine learning models using scipy and scikit-learn. With this Online Data Science with Python Training you will have the proficiency in solving real life data science problems.
Course Eligibility
- Freshers
- BE/ Bsc Candidate
- Any Engineers
- Any Graduate
- Any Post-Graduate
- Working Professionals
Syllabus Data Science with Python
PYTHON Introduction
What is Python and history of Python?
Installing Anaconda, Jupyter Notebook
First Program
Python Identifiers, Keywords and Indentation
Comments
Getting User Input
Python Data Types
What are keywords
What are variables?
Python Inbuilt Functions
Control-Flow Statements:
if-else
Elif
While loop
For loop
Range Function
Break
Assert
Pass
Return
Coding Assignment
Data Structures:
What are Data Structures?
Lists in Python
Code Walkthrough on Lists
Understanding Iterators
Tuple in Python
Code Walkthrough on Tuple
Dictionaries in Python
Code Walkthrough on Dictionaries
Sets in Python
Code Walkthrough on Sets
More examples on Data Structures
Functions:
What are functions in Python?
Defining and Calling Functions
Inbuilt Functions
User Defined Functions
Lambda Function
Split Function
Strip Function
Map Function
Filter Function
Format Function
Code Walkthrough on User Define Functions Regular Expressions Basics
Object Oriented Programming:
Why do we need Object Oriented Programming? What is a class?
What is an object? What is Self?
Constructors
Global and local variables Static and Dynamic Variables
Abstraction
Inheritance
Encapsulation
Polymorphism
Code Walkthroughs on OOP
Exception Handling and GUI :
Why do we need to handle exceptions?
Errors in Python
Compile-Time Errors
Runtime Errors
What is Exception?
try....except...else
try-finally clause
Raising an exceptions
User Defined Exceptions
Graphical User Interface in python
Tkinter
Button Widget ,Label Widget and Text Widge
Miscellaneous Topics :
SQL connection with Python using SQLITE Library
Multi-Threading and Multi-Processing
Introduction to Web-scraping
Beautiful Soup Library
Numpy Library for Data Analysis
Code Walkthrough On Numpy Library
Pandas Library for Data Analysis
Code Walkthrough On Pandas Library
Matplotlib Library for Data Analysis
Code Walkthrough On Matplotlib Library Revision Sessions
Assignment Discussions
Project Discussion:
Defining the Business Problem
Constraints
Flow Diagram
Libraries Used
Results and Conclusion
Future Scope
References
SQL
Introduction:
What is SQL?
Why do we need SQL?
What is DataBase Management System?
Types of DBMS
Execution Of SQL query
Introduction to MySQL
Installation of MySQL server
Download sample database
Load sample database to work
Difference Between SQL and MYSQL
Basic SQL Keywords:
Basic SELECT Statement
Limit/Offset
OrderBy
Distinct
Where
Comparison Operators
Null
Logical Operators
Aggregate Operators(Count, Max, Min, Avg, Sum)
Group By
Having
Order Of Keywords
Wildcard Operators
JOINS:
What are Joins?
Inner Join
Quter Join
Left Join
Right Join
Self Join
SubQueries/NestedQueries /Inner Queries
Triggers
Stored Procedures
DML/DDL
DML.:Insert
DML.:Update, Delete
DDL:Create Table
DDL.:Alter:Add,Drop,ModifyDDL.:Drop Table,
Truncate,Delete
DCL:Data Control Language: GRANT,REVOKE
Probability And Statistics Introduction
Why do we need to learn Probability and Statistics?
Descriptive Statistics
Central Tendency(Mean/Median/Mode)
Deviation(Standard Deviation/Variance)
Population and Sample
Distributions
Why do we care about Distributions?
Distributions and Various Tests:
What is Random Variable?
Discrete and Continuous Random Variable
Normal Distribution/Gaussian Distribution
PDF and CDF of Gaussian distribution
Uniform Distribution
Q-Q Test
K-S Test
What is Sampling?
Types of Sampling
Inferential Statistics:
Correlation Vs Causation
Hypothesis Testing
Confidence Interval
Permutation Resampling Test
A/B Testing
Case Studies/Project:
Case Study-1
Case Study-2
DataScience-1
Machine Learning
Industry Case Studies
DataScience Vs DataAnalysis Vs MachineLearning Vs DeepLearning DeepLearning
Introduction to Numpy, Pandas, Sci-kit Learn and Matplotlib Library Matplotlib Library
Importing data from different Sources
Basic Terminologies and Basic Maths:
Traditional Programming Vs Machine Learning
Types of Machine Learning Problems
Supervised and Unsupervised Learning
Classification and Regression
Overfitting and Underfitting
What is a point and a Vector?
Distance between 2 points, Distance between point and a line.
Equation of a line, Equation of a Plane, Equation of a hyper plane.
Dot product and Projection of one vector onto another.
Basics of Differentiation
KNN(K nearest Neighbour) Algorithm
Geometric Intuition of KNN
Mathematical Intuition of KNN
Limitations of KNN
What are Hyper-parameters?
Hyper-parameters Tuning
Why do we need Cross-Validation?
Code Walkthrough on KNN
Supervised Learning Continues:
Industry Case Studies
Naive Bayes algorithm
What is Conditional Probability
What is Naive about Naive Bayes?
Geometric Intuition of Naive Bayes
Mathematical Intuition of Naive Bayes
Limitations of Naive Bayes
Hyperparameter Tuning in Naive Bayes
Code Walkthrough of Naive Bayes
Introduction to Logistic Regression
Geometric Intuition of Logistic Regression
Mathematical Intuition of Logistic Regression
Why do we need sigmoid function?
Regularisation(L1 and L2)
Limitations of Logistic Regression
Code Walkthrough of Logistic Regression
Supervised Learning Continues:
Industry Case Studies
Introduction to Linear Regression
Geometric and Mathematical Intuition
Assumptions of Linear Regression
Limitations of Linear Regression
Code Walkthrough of Linear Regression
Optimisation Theory
Convex and Non Convex Functions
Gradient Descent
Stochastic Gradient Descent
Introduction to SVM(Support Vector Machines)
Geometric Intuition
Mathematical Intuition
Hard and Soft SVM
Kernalisation in SVM(Radial Basis Function)
Limitations of SVM
Code Walkthrough of SVM
Industry Case Studies Decision Tree and Ensembles :
Decision Tree
Geometric Intuition of Decision Tree
Mathematical Intuition of Decision Tree
Entropy and Gini Impurity
Information Gain
Limitations of Decision Tree
Code Walkthrough of Decision Tree
What is Ensembles
Bagging and Boosting
What is Ensembles?
Bagging and Boosting
Concept of Bootstrapping
Introduction to Random Forest
Variance and Bias
Geometric Intuition of Random Forest
Why Random Forest is so famous?
Code Walkthrough of Random Forest
Performance Metric and Different
Situations in Supervised Learning : Industry Case Studies
Accuracy
How to deal with the imbalance
Why Accuracy as a metric will fail in data? most of the real world cases?
Precision and Recall
F1 Score
Confusion Matrix
Log-loss
ROC-AUC Curve
RMSE(Root Mean Square Error)
R2(Coefficient of Determinant)
MAD(Median Absolute Deviation)
How to Handle Outliers in the data? How to handle categorial data?
Scaling of Features
Curse of Dimensionality
Unsupervised Learning and Dimension Reduction: Industry Case Studies
What is Unsupervised Learning?
What is Clustering?
K-Means Clustering
Hierarchal Clustering
Why Dimensions Reduction?
PCA(Principle Component Analysis)
Machine Learning Project :
Industry Case Studies
Business Problem
Contraints
Data Collection
Formulate Business Problem to Machine Learning Problem Data Cleaning
Data Preprocessing
EDA(Exploratory Data Analysis)
Modelling
Evaluating the Performance of the models
Retrain if necessary
Deployment
Artificial Intelligence With Deep Learning
History of Neural Networks:
Industry Case Studies
Who invented Neural Network?
What is the intuition of a Neural Network?
What is a perceptron?
Connecting Logistic Regression, Linear Regression with Perceptron
Multi Layer Perceptron
Training of a Perceptron
MLP and Backpropogation)
Notation
Training a MLP:Chain Rule
Training a MLP:Memoization
Back propogation Activation Functions Sigmoid
Tanh
RELU
Vanishing gradient
Deep Multi LayerPerceptrons :
Dropout and Regularisation
Batch Normalisation
Batch SGD with Momentum
Adam
Softmax and Cross-Entropy
How to train Deep MLP?
Tensorflow and Keras Overview
Install Tensorflow
Softmax Classifier on MNIST data
Code Walkthrough of MLP
Hyperparameter Tuning in Keras
Introduction to CNN Continues :
AlexNet
VGGNet
Residual Network
Inception Network
What is Transfer Learning?
Code Walkthrough of CNN
Introduction to NLP :
What is NLP(Natural Language Processing)?
BOW(Bag of Words)
Text Preprocessing: Stemming and Lemmatisation
Stop Word Removal
Tokenisation
Unigram, Bigram, Ngrams
TF-IDF
Weighted TF-IDF
Word2Vec(W2V)
Code Walkthrough of NLP Techniques
Introduction to CNN(Convolution Neural Network)
What is Convolution?
(Convolution:Padding and Strides Convolution over RGB images
Max Pooling
CNN Training
Introduction to RNN :
Why RNN(Recurrent Neural Network)?
Training RNN
Types of RNN
Need of LSTM
|. STM(Long Short Term Memory)
Deep RNN
Bidirectional RNN
Code Walkthrough of RNN
Deep Learning Project :
Business Problem Contraints
Data Collection
Formulate Business Problem to Deep Learning Problem
Data Cleaning
Data Preprocessing
EDA (Exploratory Data Analysis)
Feature Extraction
Modelling
Evaluating the Performance of the models
Retrain if necessary
Trainer Profile Data Science with Python
Our Trainers explains concepts in very basic and easy to understand language, so the students can learn in a very effective way. We provide students, complete freedom to explore the subject. We teach you concepts based on real-time examples. Our trainers help the candidates in completing their projects and even prepare them for interview questions and answers. Candidates can learn in our one to one coaching sessions and are free to ask any questions at any time.
- Certified Professionals with more than 8+ Years of Experience
- Trained more than 2000+ students in a year
- Strong Theoretical & Practical Knowledge in their domains
- Expert level Subject Knowledge and fully up-to-date on real-world industry applications
Proficiency After Training
Programmatically download and analyze data
Learn techniques to deal with different types of data – ordinal, categorical, encoding
Using I python notebooks, master the art of presenting step by step data analysis
Work with real-time data
Learn tools and techniques for predictive modeling
Validate Machine Learning algorithms
Frequently Asked Questions
Students Reviews
If you are looking for IT courses this is the right place. All kind of IT courses are available here. I have completed my Networking CCNA course from Seven Mentor Classes. Those who looking for practical knowledge must join Seven mentor Classes they teach very well they cover all the topics regarding course. Nice Environment Good Teachers.They even give the Job Placement assistance.Best coaching for Networking learning. All trainer’s who run it are very supportive along other staff and teachers. They have pure practical approach.Reasonable price and worth it!!!
- Deepa Shahare
It was good experience Data Science with Python Course at classes . Trainer was very good and have very good knowledge of Performance Testing. The course content was for basic or medium level of proficiency. One needs to also do self practice and get ones doubt or questions cleared to make best out of the course.Good theory and practical sessions. Helpful to clear basic concepts from faculty member ..the lab practice provided by the trainer is also good. Data Science with Python Course classes is the best place to expand your wisdom in Developer field. Thanks for the training and mentoring.
- Divya
It is the best institute for Data Science with Python in Pune according to me. I have completed my training few days ago. It was a great experience over here. The trainers are very knowledgeable, they helped me in clearing the basic concepts of programming. And placement team did a great job as I got placed in a good organization after completing the course. Thanks!
- Poonam
Corporate Training
As we know that the field of data science is vast and technologies are evolving rapidly and it is also getting updated every now and then. Accordingly these changes organizations also upgrade their method of implementations to cope up with the speed of evolution and in the race to serve customers with best. But because of the lack of lack of knowledge and expertise it can be hard. Corporate Data Science with Python Training will help you with it.
With SevenMentor’s Corporate Data Science with Python Course you will be able to sharpen and train your existing employees with new things in the technology. Going for Corporate Data Science with Python Training will be the best option to enhance skills of your employees with the latest ongoing technology will eventually help your organization to cope-up with the current market trends.
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