Detailed overview of data science course in Pune

1. Data Science Course in Pune
Introduction to Data Science:
Definition and scope of facts science.
Understanding the statistics science lifecycle: information acquisition, records coaching,
evaluation, modelling, and deployment
Role of statistics scientists in diverse industries
Data Collection and Data Cleaning:
Techniques for gathering facts from unique resources: databases, APIs, internet scraping, and
so on.
Data cleansing and preprocessing to ensure data pleasant
Handling missing values, outliers, and duplicates.
Data Exploration and Visualisation:
Exploratory data analysis (EDA) techniques
Data visualisation the usage of Python libraries like Matplotlib and Seaborn
Creating interactive visualisations with equipment like Tableau or Power BI
Statistical Concepts for Data Science:
Understanding basic statistical principles: suggest, median, general deviation, etc.
Probability distributions and speculation testing
Applying statistical checks to make facts-pushed decisions.
Introduction to Machine Learning:
Fundamentals of device learning: supervised, unsupervised, and reinforcement getting to know
Types of system getting to know algorithms: choice timber, linear regression, logistic regression,
ok-nearest neighbours, and so forth.
Model evaluation and performance metrics
Data Preprocessing and Feature Engineering:
Data scaling, normalisation, and transformation
Feature selection and extraction techniques
Handling specific variables and encoding.
Machine Learning Algorithms:
In-intensity study of famous device gaining knowledge of algorithms: Support Vector Machines
(SVM), Random forests, Gradient Boosting, and so forth.

2. Understanding the instinct and mathematical standards behind those algorithms
Model Selection and Hyperparameter Tuning:
Cross-validation and model choice techniques.
Optimising version performance through hyperparameter tuning
Deep Learning and Neural Networks:
Introduction to deep studying and neural networks
Building and education neural networks using libraries like TensorFlow and Keras
Applications of deep learning in laptop vision and natural language processing
Time Series Analysis:
Analysing time-based facts and forecasting destiny trends.
Popular time collection forecasting models: ARIMA, Exponential Smoothing, and many others.
Big Data and Distributed Computing:
Introduction to big statistics standards
Working with allotted computing frameworks like Hadoop and Spark
Handling massive-scale datasets using PySpark
Natural Language Processing (NLP):
Understanding and processing human language statistics
Building NLP fashions for sentiment evaluation, textual content classification, and language
generation
Model Deployment and Productionization:
Deploying device mastering fashions in production environments
Building APIs for model integration in net packages
Handling version updates and model control.
Ethics in Data Science:
Understanding the moral considerations in statistics technology
Addressing privateness, bias, and fairness problems in records-driven solutions.
Real-global Projects and Case Studies:
Working on palms-on projects to use the standards found out

3. Solving actual-global enterprise problems using statistics science strategies.
Career Guidance and Job Placement:
Resume constructing and interview practise
Job placement help and guidance for process interviews
Conclusion: A statistics technology course in Pune is a comprehensive programme that covers
numerous elements of data science, inclusive of records collection, preprocessing, exploratory
information evaluation, gadget getting to know, deep learning, and huge information processing.
The route gives fingers-on revel in thru tasks and case studies, making ready college students
for actual-world challenges within the statistics technology area. With the increasing demand for
data scientists in diverse industries, enrolling in a statistics technology direction in Pune can be
a stepping stone closer to a worthwhile and enjoyable profession on this thrilling field.