Data Science

Best Data Science course in Kochi

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Choosing IROHUB was a game-changer for me. Their comprehensive programs and hands-on approach helped me gain invaluable skills in the tech industry.

Akash T S Jr. Data Scientist


1st Floor, Trust building, Kayyath Ln, Palarivattom, Kochi, Kerala

In an era where data drives decisions across industries, the demand for skilled data scientists continues to soar. If you aspire to embark on a rewarding career in data science,iROHUB offers a comprehensive and dynamic training program that stands out as a top choice.  Irohub’s data science training program is designed to equip trainees with the knowledge, tools, and skills necessary to excel in the rapidly evolving world of data analysis and predictive modelling. The curriculum covers an extensive range  of subjects, such as:

  • Fundamentals of Data Science: Students start with a solid foundation in statistics, mathematics, and programming, providing them with the necessary groundwork to tackle complex data-related challenges.
  • Data Wrangling and Preprocessing: The course delves into data cleaning, transformation, and preparation, ensuring that students can work effectively with messy and unstructured data.
  • Machine Learning and Deep Learning: Participants gain hands-on experience with various machine learning algorithms and neural networks, enabling them to build predictive models and make data-driven decisions.
  • Big Data Technologies: The training includes exposure to big data technologies like Hadoop and Spark, equipping students to handle large datasets efficiently.
  • Data Visualization: Students learn to communicate insights effectively through data visualization tools like Tableau and Matplotlib, enhancing their ability to convey complex findings to stakeholders.
  • Real-World Projects: irohub emphasizes practical application, allowing students to work on real-world projects and case studies, ensuring they are job-ready upon completion.

 

Why Choose iROHUB for Data Science Training in Kochi?

 

  • Expert Faculty: irohub boasts a team of experienced data scientists and industry experts who bring a wealth of practical knowledge to the classroom, providing students with real-world insights and mentorship.
  • Cutting-Edge Curriculum:irohub regularly updates its curriculum to align with the latest trends and technologies in the data science field, ensuring that trainees are equipped with the most relevant skills.
  • State-of-the-Art Infrastructure: Data science training in Kochi offers a conducive learning environment with access to high-performance computing resources, well-equipped labs, and an extensive library of data science literature.
  • 100% Placement Assistance: irohub has a strong network of industry connections and offers robust placement support, helping students secure internships and job opportunities with leading organizations.
  • Flexibility and Convenience: We provide flexible training options, including full-time and part-time courses, making it accessible to working professionals and students alike.
  • Affordable Tuition: Compared to many other institutions, irohub offers competitive fees, ensuring that quality data science education is within reach.

 

Choosing IROHUB for your data science training is a strategic decision that can propel your career in this high-demand field. With an updated curriculum, expert faculty, practical projects, and strong placement support, We ensure that you are well-prepared to meet the challenges of the data-driven world. If you are passionate about transforming data into actionable insights and want to be at the forefront of innovation, data science course in Kochi is the ideal choice to start your data science journey.

 

Modules:

- Basics of Python Programming - Conditional and Looping Statements - Datatypes - Functions - Modules and Packages - Object Oriented Programming Principles - Exception Handling Mechanisms - Assessment
- Introduction to Relational Databases - SQL (Structured Query Language) and commands - Types of Joins - Subqueries, aggregation functions, GROUP BY, HAVING clauses - Overview on NoSQL Databases - Assessment
- Introduction to Numpy - Creating Arrays using Numpy - Random Numpy Arrays - Array Operations - Advanced Indexing Concepts - Assessment
- Introduction to Pandas - Series in Pandas - DataFrames in Pandas - Operations with DataFrames - Conditional Filtering techiniques in Pandas - Handling Missing Datas - Groupby Operations - Data Preprocessing Methods - Reading datas of different File Formats through Pandas
- Basics of Matplotlib - Types of Plots - Customizing Plots - Creating Multiple Subplots - Advanced Plotting Techniques - Exporting and Saving Plots - Matplotlib Styles and Themes - Integration with other Libraries - Assessment
- Introduction to Seaborn - Data Visualization options with Seaborn - Customization and Styling - Integration with Pandas and Matplotlib - Assessment
- Introduction to Machine Learning - Differences between AI, ML, Data Science and Deep Learning - Overview on Supervised and Unsupervised Learning Techniques - Introduction to Regression and Classification basics - Overview on Clustering and Dimensionality Reduction principles - Assessment
- Linear Regression - Polynomial Regression - Logistic Regression - K-Nearest Neighbours Algorithm - Ridge & Lasso Regression - Support Vector Machines - Decision Trees - Random Forests - Bagging and Boosting Techniques - Assessment
- K-Means Clustering - Hierarchical Clustering - DBSCAN Clustering - Principal Component Analysis(PCA) - Assessment
- Introduction to Bayes Theorem - Named entity recognition (NER). - Bag-of-words model - TF-IDF (Term Frequency-Inverse Document Frequency) - Processsing Text Data for Sentiment Analysis - Assessment
- Neural Network Basics - Perceptrons and multi-layer perceptrons (MLPs) - Activation functions - Backpropagation and Forwardpropogation algorithm - Convolutional Neural Networks (CNNs) for image data - Recurrent Neural Networks (RNNs) for sequential data - Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) - Autoencoders and Variational Autoencoders (VAEs) - Assessment