Understand the concepts of the Python Language.

Learn various sequence structures their usage, and execute sequence operations.

understand diverse types of Functions and various Object-Oriented concepts such as Abstraction, Inheritance, Polymorphism, Overloading, Constructor, and so on.

Discover how to create generic python scripts, address errors/exceptions in code, and extract/filter content using regex.

Learn the basics of Data Analysis using two essential libraries: NumPy and Pandas.

know about analyzing datasets and data manipulation using Pandas.

learn about Data Visualization using Matplotlib.

learn GUI programming using the ipywidgets package.

learn to design Python Applications.

design Python Applications.

you will be introduced to Data Science how it helps analyze large and unstructured data with different tools.

Learn sources available to extract data, arrange the data in a structured form, analyze the data, and represent the data in a graphical format.

understands the concept of Machine Learning with Python and its types.

learn Supervised Learning Techniques and their implementation.

learn about the effect of dimensions within data.

learn Supervised Learning Techniques and their implementation.

knows about Unsupervised Learning, and the various types of clustering used to analyze the data.

learn Association rules and their extension.

learn about developing an intelligent learning algorithm.

know about Time Series Analysis to forecast dependent variables based on time.

understand selecting one Model over another, Boosting and its importance in Machine Learning.

implement a Project end to end, and the Expert will share his insights from the Industry to help you with your career in this profession. After that, we will have a Q&A and doubt clearing session.

Learn text mining and the ways of extracting and reading data from some common file types, including NLTK corpora

Learn some ways of text extraction and cleaning using NLTK.

comprehend to study a sentence structure using a word group to construct phrases and sentences using NLP and English grammar rules.

review text classification, vectorization techniques, and processing using scikit-learn.

learn to create a Machine Learning classifier for text classification

understand Sentiment Classification on Movie Rating Dataset

Learn about Big Data, Hadoop, and Spark.

Know Python programming basics and learn different types of sequence structures, related operations, and their usage.

Discover How to create generic python scripts, how to address errors/exceptions in code, and how to extract/filter content using regex.

Learn about Apache Spark and its components.

know about Spark - RDDs and other RDD related manipulations for implementing business logic

learn about SparkSQL, data-frames, datasets in Spark SQL, and different kinds of SQL operations performed on the data-frames.

Learn about Machine Learning techniques/algorithms and their implementation using Spark MLlib.

implement various algorithms supported by MLlib.

Learn about Kafka and Kafka Architecture.

Learn about Spark streaming DStreams and their Transformations.

discover about the different streaming data sources such as Kafka and flume.

A bank is attempting to broaden the financial inclusion for the unbanked population by providing a good and secure borrowing experience. To ensure this underserved population has a good loan experience, it uses various alternative data--including telco and transactional information--to predict their clients' repayment abilities. The bank has asked you to develop a solution to ensure that clients capable of repayment are accepted and that loans are given with a principal, maturity, and repayment calendar to empower their clients to succeed.

Analyze and deduce the best-performing movies based on customer feedback and review. Use two different APIs (Spark RDD and Spark DataFrame) on datasets to find the best ranking movies.

Learn fundamental concepts of Spark GraphX programming concepts and operations along with different GraphX algorithms and their implementations.

Learn what Python is and its basics.

Learn various types of sequence structures, related operations, and their usage.

Learn to create generic python scripts, address errors/exceptions in code, and extract/filter content using regex.

Understand the Object-Oriented Programming

Learn to use databases and what a project skeleton looks like in Python.

Know about Django and learn to create views and perform URL mapping.

create Templates and Forms in Django