Machine Learning Certification Training using Python
CertOcean's Machine Learning Certification Training using Python has
been designed and implemented to provide you with in-depth knowledge of
various machine learning algorithms such as regression, clustering,
decision trees, random forest, Naïve Bayes and Q- Learning. With this
course, you don't need any prior Programming Experience or experience
with Python, as we will be covering all the topics that you need to
boost your command over the subject and be in a high-demand. This Course
will help you become a certified Machine Learning Developer by
exploring various concepts in and around Machine Learning like
supervised, unsupervised, and reinforcement algorithms. By the end of
this course, you will be able to demonstrate professional know-how
around the essential concepts and functionalities across Machine
Learning with Python with complete hands-on.
Why should you take the Machine Learning Certification Training using Python?
* Data scientist is one of the most lucrative job opportunities with a median job salary of $242,000. Moreover, several job openings in the same field make you a highly necessary candidate with modern skills.
* Candidates can take up roles like chief data scientist and chief analytics officers that specialize in analytical skills and drive quality business decisions.
* In the coming time, more and more businesses will need data scientists for the increasing business data needs.
Learning Objective: Understand how to analyze large and unstructured data with different tools.
* What is Data Science?
* What does Data Science involve?
* The Era of Data Science
* Business Intelligence VS Data Science
* The Life cycle of Data Science
* Tools of Data Science
* Introduction to Python
Learning Objective: Learn about how to extract data, arrange it into structured data, and represent the data in a graphical format.
* Data Analysis Pipeline
* What is Data Extraction
* Types of Data
* Raw and Processed Data
* Data Wrangling
* Exploratory Data Analysis
* Visualization of Data
* Python Revision, including 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 is 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
* Factor Analysis
* Scaling dimensional model
* 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
* How to Implement 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 do 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
* What is Time Series Analysis?
* Importance of TSA
* Components of TSA
* White Noise
* AR model
* MA model
* ARMA model
* ARIMA model
* ACF & PACF
* What is Model Selection?
* Need of Model Selection
* Cross –Validation
* What is Boosting?
* How Boosting Algorithms work?
* Types of Boosting Algorithms
* Adaptive Boosting
Our Machine Learning Certification using Python is designed to help candidates understand the concept of machine learning. This training provides you with a deep understanding of machine learning, its importance, and its implementation in the Python programming language. Opting for machine learning certification online will teach you about reinforcement learning, which in fact, is an important aspect of Artificial Intelligence. Moreover, you will be able to work on real-life scenarios using machine learning algorithms.
After completing the machine learning certification, you will be able to:
? Derive insights into the 'Roles' played by a Machine Learning professional
? Data analysis using python Automation
? Proper description for Machine Learning
? Work with real-time data
? Study tools and techniques for predictive modeling
? Discuss Machine Learning algorithms, implementation, and applications
? Validate Machine Learning algorithms
? Explain Time Series
Who should opt for this Machine Learning Certification Training using Python?
? Developers meaning to be a ‘Machine Learning Engineer'
? Analytics Managers who are leading a team of technical analysts
? Business Analysts who want to know Machine Learning (ML) Techniques
? Information Architects who want to realize expertise in Predictive Analytics
? 'Python' professionals who want to style automatic predictive models
Instructor-led live sessions
Online Live Training is for 36 Hours
Weekend class : 12 sessions of 3 hours each and Weekday class : 18 sessions of 2 hours each.
Real-life Case Studies
Live project based on any of the selected use cases, involving implementation of Data Science with Python.
Each class will be followed by practical training sessions for a better hands-on experience.
Students will get lifetime access to all the course materials where presentations, quizzes, installation guides, and class recordings are available.
24/7 expert support
We provide 24/7 support to all the students, thereby resolving technical queries.
Once you successfully complete your final project, you will receive the Machine learning certification using Python from CertOcean.
Frequently Asked Questions (FAQs):
There are no prerequisites for the Course, and you only require a good Internet Connection with a Laptop to undertake this Course.