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Why enroll for Applied Machine Learning with Python by PwC Academy?
Applied Machine Learning with Python by PwC Academy Training Benefits
As the ML market is expected to expand 36.08% to US$503.40 billion by 2030, our Applied Machine Learning with Python by PwC Academy course provides learners with the necessary skills to capitalize on the increasing demand for skilled professionals in this field. Thus, learners can bridge the skills gap and improve their career prospects in this swiftly evolving field.
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Why Applied Machine Learning with Python by PwC Academy from edureka
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- Expert-Led Mentoring Sessions
- Instant doubt clearing
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- Course Access Never Expires
- Free Access to Future Updates
- Unlimited Access to Course Content
24x7 Support
- One-On-One Learning Assistance
- Help Desk Support
- Resolve Doubts in Real-time
Hands-On Project Based Learning
- Industry-Relevant Projects
- Course Demo Dataset & Files
- Quizzes & Assignments
Industry Recognised Certification
- Edureka Training Certificate
- Graded Performance Certificate
- Certificate of Completion
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About your Applied Machine Learning with Python by PwC Academy
Skills Covered
Tools Covered
Applied Machine Learning with Python by PwC Academy Curriculum
Curriculum Designed by Experts
Data Exploration and Processing with Python
9 Topics
Topics
- Introduction to Python for Data Handling (Pandas, NumPy)
- Data Cleaning and Preprocessing Techniques
- Handling Missing and Duplicated Data
- Data Types and Type Conversion
- Exploratory Data Analysis (EDA)
- Aggregation and Grouping Operations
- Merging and Joining Datasets
- Working with Date and Time Data
- Introduction to Data Science Concepts
![skill]( "Hands On Experience")
- Reading and writing CSV files
- Handling missing values
- Aggregation and analysis
![skill]( "skill you will learn")
- Data Wrangling
- Python Programming
- Exploratory Data Analysis
Machine Learning for Churn Prediction
9 Topics
Topics
- Overview of Supervised Learning (Classification)
- Algorithms: Logistic Regression, Decision Trees, Random Forests
- Feature Engineering Techniques
- Handling Missing Data and Encoding Categorical Variables
- Scaling and Normalization of Features
- Dimensionality Reduction Techniques (PCA, t-SNE)
- Training and Evaluating Supervised Models
- Cross-validation and Hyperparameter Tuning
- Model Interpretation and Feature Importance
![skill]( "Hands On Experience")
- Data preparation and exploration
- Implementing supervised learning for customer churn prediction
- Dimensionality reduction
![skill]( "skill you will learn")
- Supervised Learning
- Feature Engineering
- Dimensionality Reduction
Data-Driven Insights with Clustering
9 Topics
Topics
- Introduction to Unsupervised Learning
- Overview of Clustering Techniques (K-Means, Hierarchical, DBSCAN)
- Data Preprocessing for Clustering (Scaling, Normalization)
- Clustering Algorithms: Theory and Application
- Visualizing Clusters (PCA, t-SNE)
- Evaluating Clustering Results (Silhouette Score, Elbow Method)
- Handling Outliers and Anomalies in Clustering
- Business Applications of Customer Segmentation
- Interpreting and Presenting Clustering Insights
![skill]( "Hands On Experience")
- Applying clustering algorithms
- Model evaluation
![skill]( "skill you will learn")
- Clustering Techniques
- Data Preprocessing
- Unsupervised Learning
Inventory Management Optimization with Reinforcement Learning
9 Topics
Topics
- Introduction to Reinforcement Learning (RL) Concepts
- Overview of RL Algorithms
- Defining the RL Environment
- Inventory Management Challenges and Strategies
- Stock Replenishment and Demand Forecasting
- Formulating the RL Problem for Inventory Management
- Training and Tuning RL Models for Optimization
- Evaluating RL Model Performance
- Comparing RL Models with Traditional Inventory Methods
![skill]( "Hands On Experience")
- Implementing RL model
- Evaluating model performance
![skill]( "skill you will learn")
- Reinforcement Learning
- Optimization Techniques
- Inventory Management
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Applied Machine Learning with Python by PwC Academy Course Details
About PwC Academy
PwC Academy is a learning and education service offering of PwC India. It provides diverse training courses based on the best practices of PwC’s global network of firms and brings real-life business experiences into the classroom. Moreover, subject matter experts help to make learning more effective and practical.
PwC Academy focuses on improving the knowledge, skills, competence, and expertise of professionals and students by offering diverse learning programs in areas such as financial accounting and reporting, risk, governance, and digital.
About this Applied Machine Learning with Python by PwC Academy Course
This course emphasizes the use of Python to transform and shape data according to be utilized in machine learning models. Learners will learn to use supervised and unsupervised learning to predict customer attrition and segment them according to strategies.
The application scenarios will focus on practical, real-world uses, such as predicting customer churn, segmenting them, and designing reinforcement models for inventory management.
What will you learn from this Applied Machine Learning with Python by PwC Academy?
By the end of the course, you will be able to:
- Explain the purpose and importance of data analysis according to industry standards
- Describe supervised learning algorithms and their application in predicting customer churn
- Use methods for reducing dimensions to improve model accuracy and effectively handle data with high dimensions
- Examine customer data using clustering algorithms to identify patterns and segments
- Evaluate and implement reinforcement learning techniques to optimize inventory management.
- Assess the effectiveness of RL models in enhancing decision-making for stock replenishment and reducing costs.
What is Python?
Python is a widely used programming language for small and large-scale projects. Python allows you to integrate web development with data analysis seamlessly. Python's wide adoption is due in part to its standard library, accessibility, and support for multiple paradigms, such as procedural, functional, and object-oriented programming styles. Python modules can interact with many databases, making it an excellent choice to learn data science and machine learning.
What is machine learning?
Machine learning is a subset of artificial intelligence (AI) that allows computers to enhance their performance on specific tasks by learning from data without the need for explicit programming. Machine learning systems analyze data patterns, generate predictions, and adjust to new information through the use of statistical models and algorithms.
What is the scope of Applied Machine Learning with Python in industries?
The extent of Applied Machine Learning with Python in various sectors is broad and continuously growing, fueled by the rising dependence on data-driven decision-making. Organizations in various industries like finance, healthcare, retail, and technology use machine learning to boost predictive analytics, streamline operations, and enhance customer satisfaction. Machine learning models have the ability to enhance supply chains, identify fraud, tailor marketing techniques, and improve operations, resulting in notable savings and increased efficiency.
What are the roles and responsibilities of machine learning engineers?
The following are the responsibilities of machine learning engineers:
- Data Preprocessing: The process of cleaning and organizing data in preparation for model training.
- Model Development: The design and training of machine learning models.
- Feature Engineering: The process of generating and selecting pertinent features to improve the performance of a model.
- Model Evaluation: Utilizing a variety of metrics to evaluate the efficacy of the model.
- Deployment: The process of integrating models into production environments.
- Monitoring and Maintenance: Guaranteeing that models operate efficiently and providing retraining as required.
These positions are indispensable for optimizing processes and utilizing data to inform decision-making. information.
Who is this Applied Machine Learning with Python by PwC Academy for?
This Applied Machine Learning with Python by PwC Academy is specifically designed for:
- Professionals aiming to enhance their skills and demonstrate their expertise in machine learning domain.
- Machine learning and data science professionals
- Technical Leads
- AI Enthusiasts
- Freshers
What are the prerequisites for this Applied Machine Learning with Python by PwC Academy?
A fundamental understanding of machine learning concepts paired with Python coding skills, especially with AI and ML libraries will be beneficial for the learners.
What are the system requirements for this Applied Machine Learning with Python by PwC Academy?
The following specifications are the recommended system requirements for this Applied Machine Learning with Python by PwC Academy :
- Operating System: Any modern operating system that supports the required tools and services (e.g., Windows, macOS, Linux).
- Processor: For optimal performance, it is recommended to have a 64-bit processor with a minimum speed of 2GHz or higher.
- Memory (RAM): It is advisable to have at least 8 GB of RAM to run multiple virtual machines, containers, and development environments simultaneously.
- Storage: There must be sufficient free storage space for installing various development tools and other required software components. At least 20 GB of free space is advisable.
- Browser: Compatibility with modern web browsers for accessing online resources, documentation, and web-based tools used in the course.
These system requirements provide a suitable environment for completing the tasks and exercises outlined in the Applied Machine Learning with Python by PwC Academy . Adjustments may be necessary based on specific preferences, additional software requirements, or constraints.
How will I execute the practicals during this Applied Machine Learning with Python by PwC Academy?
Detailed step-by-step installation guides are available on the LMS. If you have any doubts, the 24/7 support team will promptly assist you.
Certification
To unlock the course completion certificate from PwC Academy and Edureka, you must ensure the following:
- Completely participate in this Applied Machine Learning with Python by PwC Academy.
- You must complete all modules along with the graded assessments.
The growing demand for experienced professionals in a variety of industries has made machine learning a promising career path. It provides a variety of job opportunities, a high earning potential, and the opportunity to contribute to innovative initiatives that have the potential to have a significant impact on society. Furthermore, the field offers a dynamic environment that fosters the development of skills and the acquisition of new knowledge, rendering it an exciting option for individuals who are enthusiastic about data and technology.
Beginners are welcome to enroll in this course, as all concepts will be taught from the ground up. This will make an individual highly proficient in managing complex tasks encountered in industries. The class provides a strong base in machine learning applications.
The value of obtaining a certification in Applied Machine Learning with Python Certification is multi-faceted:
- Enhanced Career Opportunities: A recognized machine learning certification endorses candidate’s knowledge, leading to increased earning potential in a variety of industries and jobs.
- Skill Validation: Machine Learning certification verifies the candidate’s skills and knowledge of the domain.
- Industry Recognition: Employers frequently seek candidates with accredited certificates. A generative AI certification indicates a candidate’s commitment to staying current in the area.
Tech giants such as Google, Amazon, and Microsoft, as well as financial firms like JPMorgan Chase and Goldman Sachs, are among the numerous prominent organizations that are currently recruiting professionals who are proficient in Machine Learning. ML professionals are also sought by consulting firms like Deloitte and Accenture, as well as startups and healthcare organizations, to optimize operations and improve data-driven decision-making.
John Doe
for having completed the program on
Title
in association with the PwC Academy
issued on
31st Jul 2024
Title
in association with the PwC Academy
issued on
31st Jul 2024
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Applied Machine Learning with Python by PwC Academy FAQs
What if I miss the Applied Machine Learning with Python by PwC Academy classes?
You will never miss a lecture at Edureka! as you can always view the recorded session of the class available in your LMS.
So, what are you waiting for? Enroll with Edureka and learn from the best Applied Machine Learning with Python by PwC Academy with India's top instructors.
Can I change the batch after enrolling in this Applied Machine Learning with Python by PwC Academy?
No, we don't allow batch changes as it impact your learning and career goals.
What is the role of PwC Academy in this Applied Machine Learning with Python by PwC Academy?
PwC Academy designed and developed this Applied Machine Learning with Python Course and will conduct the master class.
What is the refund policy for Applied Machine Learning with Python by PwC Academy?
This Applied Machine Learning with Python by PwC Academy, offered jointly by PwC and Edureka, is non-refundable.
What if I have queries after I complete this Applied Machine Learning with Python by PwC Academy?
Your access to the Support Team is for a lifetime and will be available 24/7. The team will help you resolve queries during and after the completion of this certification course.
How soon after signing up would I get access to the Learning Content?
Post-enrolment, the LMS access will be instantly provided to you and will be available for a lifetime. You can access the complete set of previous class recordings, PPTs, PDFs, and assignments. Moreover, access to our 24×7 support team will be granted instantly. You can start learning right away.
Will the course material be available to learners after completion of the course?
Yes, once you enroll in the Applied Machine Learning with Python by PwC Academy, you will have lifetime access to the material.
Who are the instructors for this Applied Machine Learning with Python by PwC Academy?
All the instructors at Edureka are industry practitioners with a minimum of 10-12 years of relevant IT experience. They are subject matter experts trained by Edureka to provide an excellent learning experience to the participants.
Is this course 100% online? Do I need to attend any physical classes?
This course is 100% online, and there will be no physical classes. It can be accessed through the web on any device.
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