Complete Machine Learning With Real-World Deployment
What you'll learn
- Learn the concepts of Python,Machine learning, Deep Learning,Time series. Implement Real World Projects with Proof Of Concept
- This course consists of 25+ hours video content and Downloadable files for all videos
- Data Scientists need to have a solid grasp of ML
- 5 Different Practical Data Science projects with I python Notebooks
Requirements
- There is no specific prerequisite to learn machine learning. But you need to be from engineering/science/Maths/Stats background to understand the theory and the techniques used. You need to be good in mathematics. If you are not, still you can machine learning, but you will face difficulty when solving complex real world problems. Many say you need to know Linear algebra, Calculus etc. etc. but I never learnt it, yet I am able to work on machine learning.
Description
Interested in the field of Machine Learning? Then this course is perfect for you!
Designed by professional data scientists, this course offers a clear and engaging path to mastering complex machine-learning concepts, algorithms, and coding libraries.
Discover a comprehensive roadmap connecting key machine learning ideas, practical learning methods, and essential tools.
Machine learning has a real-world impact:
Healthcare: Assisting in disease diagnosis and treatment recommendations.
Transportation: Optimizing traffic flow with tools like Google Maps.
Python is the language of choice for data scientists. This course will guide you from Python basics to advanced deep learning techniques.
Uncover the world of AI through four key sections:
Python: Build a strong foundation with data structures, libraries, and data preprocessing.
Machine Learning: Master regression, classification, clustering, and NLP.
Deep Learning: Explore neural networks, CNNs, RNNs, and more.
Time Series Analysis: Gain insights from sequential data.
Learn by doing with hands-on exercises and real-world projects.
Who is this course for?
Aspiring data scientists and machine learning enthusiasts
Students seeking a career in data science
Data analysts looking to advance their skills
Anyone passionate about using data to drive business value
Join us on this exciting journey! I'm Akhil Vydyula, an Associate Consultant at Atos India specializing in data analytics and machine learning in the BFSI sector. With a passion for data-driven insights, I'm excited to share my knowledge and experience with you. Let's explore the world of machine learning together!
Who this course is for:
- Beginner into Machine Learning
- Beginner into Python
- Non CS Students
- Career transition from Non Technical into Data Science
- Fresher to get job into Machine Learning Engineer
Instructor
- 4.0 Instructor Rating
- 1,174 Reviews
- 72,595 Students
- 45 Courses
Hello, I'm Akhil Vydyula — Lead Data Engineer at Publicis Sapient, and Former Senior Data Scientist at PwC.
With over 5 years of rich industry experience and a strong focus on the BFSI sector, I’ve led and delivered end-to-end data and analytics solutions that power strategic decisions and transform business outcomes.
At Publicis Sapient, I currently lead complex data engineering initiatives, leveraging my deep expertise in cloud-native platforms like AWS to architect robust, scalable data pipelines. My work spans across developing and optimizing ETL workflows using PySpark and Spark SQL, orchestrating data flows via EMR, Step Functions, and EventBridge, and driving real-time and batch data processing into PostgreSQL (RDS/Redshift) environments. I've also implemented AWS Glue and DMS to seamlessly replicate and transform large-scale on-premise data into cloud-native formats.
Previously, at PwC, I specialized in advanced analytics and machine learning within the Advisory Consulting practice. I’ve built and deployed predictive models using statistical analysis, regression, classification, clustering, and text mining—particularly for risk identification and decision modeling. My passion lies in transforming raw data into actionable insights through effective data storytelling and visualization.
In parallel to my corporate career, I bring over 5 years of teaching experience, mentoring hundreds of aspiring data professionals. I’m deeply committed to helping students break into the data industry by translating real-world challenges into practical learning experiences.
Whether it's building data pipelines, uncovering business insights, or shaping the next generation of data talent, I thrive at the intersection of technology, strategy, and impact.
Let’s connect if you're passionate about data, eager to learn, or looking to collaborate on meaningful, data-driven initiatives.