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- Learn through high quality presentations, quizzes, recordings of live classes; installation guide available in LMS
- Course content created using real life case studies and live project
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Python for Data Science Certification Training in Frankfort
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Preferred language for new technologies such as Data Science and Machine Learning
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A gateway towards your Data Science career
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Become a master in important Python programming concepts such as data operations, file operations and various Python libraries such as Pandas, Numpy, Matplotlib which are essential for Data Science
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We provide great learning experience at lowest price in the industry
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Exclusive Buy 1 - Get 1 Free Offer (till 31st May, 2021) Know More
Online Self-Learning
USD 299 179
40
Live-Virtual Class
Date :
May 10 Jun 07 (Weekdays)
Details
Time : 10:00 AM to 12:00 PM (CDT)
USD 699 579
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Date :
May 28 Jul 10 (Weekend)
Details
Time : 08:30 PM to 11:30 PM (CDT)
USD 699 579
May 28Fri May 29Sat Jun 04Fri Jun 05Sat Jun 11Fri Jun 12Sat Jun 18Fri Jun 19Sat Jun 25Fri Jun 26Sat Jul 02Fri Jul 03Sat Jul 09Fri Jul 10Sat
Date :
Jun 13 Jul 11 (Custom)
Details
Time : 08:30 PM to 10:30 PM (CDT)
USD 699 579
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Date :
Jun 26 Aug 08 (Weekend)
Details
Time : 10:00 AM to 01:00 PM (CDT)
USD 699 579
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Python for Data Science Certification Course Overview
Python Certification Training for Data science course helps you gain expertise in Quantitative Analysis, data mining, and the presentation of data to see beyond the numbers by transforming your career into Data Scientist role. You will use libraries like Pandas, Numpy, Matplotlib, Scikit and master the concepts like Python Machine Learning Algorithms such as Regression, Clustering, Decision Trees, Random Forest, Naïve Bayes and Q-Learning and Time Series. Throughout the Course, you’ll be solving real-life case studies on Media, Healthcare, Social Media, Aviation, HR and so on. Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. For over a decade, Python has been used in scientific computing and highly quantitative domains such as finance, oil and gas, physics, and signal processing.
Our Python Certification Training not only focuses on fundamentals of Python, Statistics and Machine Learning but also helps one gain expertise in applied Data Science at scale using Python. The training is a step by step guide to Python and Data Science with extensive hands on. The course is packed with several activity problems and assignments and scenarios that help you gain practical experience in addressing predictive modeling problem that would either require Machine Learning using Python. Starting from basics of Statistics such as mean, median and mode to exploring features such as Data Analysis, Regression, Classification, Clustering, Naive Bayes, Cross Validation, Label Encoding, Random Forests, Decision Trees and Support Vector Machines with a supporting example and exercise help you get into the weeds.
After completing this Data Science Certification training, you will be able to:
- Programmatically download and analyze data
- Learn techniques to deal with different types of data – ordinal, categorical, encoding
- Learn data visualization
- Using I python notebooks, master the art of presenting step by step data analysis
- Gain insight into the 'Roles' played by a Machine Learning Engineer
- Describe Machine Learning
- Work with real-time data
- Learn tools and techniques for predictive modeling
- Discuss Machine Learning algorithms and their implementation
- Validate Machine Learning algorithms
- Explain Time Series and its related concepts
- Perform Text Mining and Sentimental analysis
- Gain expertise to handle business in future, living the present
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Python for Data Science Certification Course Topics
- Overview of Python
- The Companies using Python
- Different Applications where Python is used
- Discuss Python Scripts on UNIX/Windows
- Values, Types, Variables
- Operands and Expressions
- Conditional Statements
- Loops
- Command Line Arguments
- Writing to the screen
- Python files I/O Functions
- Numbers
- Strings and related operations
- Tuples and related operations
- Lists and related operations
- Dictionaries and related operations
- Sets and related operations
- Functions
- Function Parameters
- Global Variables
- Variable Scope and Returning Values
- Lambda Functions
- Object-Oriented Concepts
- Standard Libraries
- Modules Used in Python
- The Import Statements
- Module Search Path
- Package Installation Ways
- Errors and Exception Handling
- Handling Multiple Exceptions
- NumPy - arrays
- Operations on arrays
- Indexing slicing and iterating
- Reading and writing arrays on files
- Pandas - data structures & index operations
- Reading and Writing data from Excel/CSV formats into Pandas
- matplotlib library
- Grids, axes, plots
- Markers, colours, fonts and styling
- Types of plots - bar graphs, pie charts, histograms
- Contour plots
- Basic Functionalities of a data object
- Merging of Data objects
- Concatenation of data objects
- Types of Joins on data objects
- Exploring a Dataset
- Analysing a dataset
- Python Revision (numpy, Pandas, scikit learn, matplotlib)
- What is Machine Learning?
- Machine Learning Use-Cases
- Machine Learning Process Flow
- Machine Learning Categories
- Linear regression
- Gradient descent
- What are Classification and its use cases?
- What is Decision Tree?
- Algorithm for Decision Tree Induction
- Creating a Perfect Decision Tree
- Confusion Matrix
- What is Random Forest?
- Introduction to Dimensionality
- Why Dimensionality Reduction
- PCA
- Factor Analysis
- Scaling dimensional model
- LDA
- What is Naïve Bayes?
- How Naïve Bayes works?
- Implementing Naïve Bayes Classifier
- What is Support Vector Machine?
- Illustrate how Support Vector Machine works?
- Hyperparameter Optimization
- Grid Search vs Random Search
- Implementation of Support Vector Machine for Classification
- What is Clustering & its Use Cases
- What is K-means Clustering
- How does K-means algorithm work
- How to do optimal clustering
- What is C-means Clustering
- What is Hierarchical Clustering
- How Hierarchical Clustering works
- What are Association Rules?
- Association Rule Parameters
- Calculating Association Rule Parameters
- Recommendation Engines
- How does Recommendation Engines work?
- Collaborative Filtering
- Content-Based Filtering
- What is Reinforcement Learning
- Why Reinforcement Learning
- Elements of Reinforcement Learning
- Exploration vs Exploitation dilemma
- Epsilon Greedy Algorithm
- Markov Decision Process (MDP)
- Q values and V values
- Q - Learning
- α values
- What is Time Series Analysis?
- Importance of TSA
- Components of TSA
- White Noise
- AR model
- MA model
- ARMA model
- ARIMA model
- Stationarity
- ACF & PACF
- What is Model Selection?
- The need for Model Selection
- Cross-Validation
- What is Boosting?
- How Boosting Algorithms work?
- Types of Boosting Algorithms
- Adaptive Boosting
Python for Data Science Certification & Exam
Once you are successfully through the project (reviewed by an expert), you will be awarded with Python for Data Science Professional Certificate.
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Most Popular
More than 10000 satisfied learners have taken this course to get certified as Python for Data Science expert.
Convenient Schedule
We have batches both on weekends and weekdays to accommodate the need of different professionals.
Low Cost
Without compromising on quality, we have priced our Python for Data Science training courses very competitively. We guarantee that you will find us more economical than other training providers.
Unmatched Quality
We along with our affiliate partners are dedicated in creating the best quality study materials and student experience across our products. All content complies with quality conformance standards to ensure that our content is the best in class and free of any errors.
Course Design
Based on years of experience in delivering effective professional training, our courses are designed not only to provide you the Python for Data Science certification, but also to empower with best practices. We achieve this by providing a unique blend of concepts, case studies, and simulations that guarantee our students know how to implement Python for Data Science in their organization.
Trainers
All our trainers are highly qualified and certified in various industry frameworks. On an average, they have 10+ years of professional experience in their respective fields. Our trainers are not only experts in their domains but are also passionate about sharing their knowledge and expertise with other professionals thereby enriching careers of students.
Never miss a class
In case you miss a session because of any reason, you can either attend the missed session in any other live batch or view the recorded session in the LMS.
Lifetime Access
You get lifetime access to the Learning Management System (LMS). Class recordings and presentations can be viewed online from the LMS.
Cloud Lab
Cloud Lab has been provided to ensure you get real-time hands-on experience to practice your new skills on a pre-configured environment.
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Python for Data Science Training Frequently Asked Questions
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