DSA Labs is a unit of i-POINT focussed on developing talent in Data Science and Analytics. We have a rich portfolio of short-term training courses in Data Science and Analytics aimed at creating industry ready professionals in BI, data analytics and decision roles.
With fast paced technological advances shaping the market dynamics, businesses will need to be agile and adaptive in order to survive and thrive. In this context, the role of BI and Analytics is ever increasing and thus creating immense career opportunities for people with the right skills and aptitude.
We at DSA Labs aim to develop talent that is needed for the industry and also fulfil career aspirations of people looking for a bright future in the field of data analytics.
Since we started i-POINT in 2008, we have a track record of training over 15,000 plus students in professional skills needed by industry and our alumni have been working for Tier-1 global companies in India and abroad.
Our proven hands-on minds-on training approach is guaranteed to deliver best returns on your investment. The following are key characteristics of every course/program at DSA Labs
Data Analysis and Visualization (CDAV) |
Job Skills Covered SQL for data analysis, data import, data cleaning, data transformations, data integration, data grouping and summarization, data pivoting, data analysis and visualization, computing measures and metrics using Excel and Power BI, creating reports and dashboards Tools: Duration: Regular batch(3 months) |
Python Foundations for Data Science and Analytics |
Job Skills Covered Python programming fundamentals, data import, data cleaning, data transformations, data integration, data grouping and summarization, data pivoting, data analysis and visualization, computing measures and metrics using Python data analysis libraries - Pandas, NumPy, Matplotlib, Seaborn Tools: |
R Foundations for Data Science and Analytics |
Job Skills Covered R programming fundamentals, data import, data cleaning, data transformations, data integration, data grouping and summarization, data pivoting, data analysis and visualization, computing measures and metrics using R modules - base, dplyr, ggplot2 Tools: |
Applied Statistical Analysis & Modelling in MS-Excel |
Job Skills Covered Exploratory analysis, descriptive statistical measures, frequency distributions, inferential statistics, statistical estimation and hypothesis testing, regression analysis - linear and logistic regression models, MLS/MLE approaches, forecasting models for time series data, Evaluating models Tools: |
Applied Statistical Analysis & Modelling in R |
Job Skills Covered Exploratory analysis, descriptive statistical measures, frequency distributions, inferential statistics, statistical estimation and hypothesis testing, regression analysis - linear and logistic regression models, MLS/MLE approaches, forecasting models for time series data, Evaluating models Tools: |
Applied Statistical Analysis & Modelling in Python |
Job Skills Covered Exploratory analysis, descriptive statistical measures, frequency distributions, inferential statistics, statistical estimation and hypothesis testing, regression analysis - linear and logistic regression models, MLS/MLE approaches, forecasting models for time series data, Evaluating models Tools: |
Applied machine learning in Python |
Job Skills Covered Machine learning approach to predictive modelling, supervised learning, unsupervised learning, applied ML algorithms (instance based, tree based, neural network, ensemble methods) to numerical predictions and classification problems, model evaluation, performance metrics, optimizing model parameters, performance estimation and tuning Tools: |
Applied machine learning in R |
Job Skills Covered Machine learning approach to predictive modelling, supervised learning, unsupervised learning, applied ML algorithms (instance based, tree based, neural network, ensemble methods) to numerical predictions and classification problems, model evaluation, performance metrics, optimizing model parameters, performance estimation and tuning Tools: |
Natural Language Text Processing in Python |
Job Skills Covered Text import, pre-processing text -text cleaning, stop words removal, text tokenization, text normalization (stemming and lemmatization), vectorization, text clustering and classification using machine learning methods, case studies in sentiment analysis using nltk and spacy, packaging trained models Tools: |
DSA Labs
A unit of i-POINT
4-8-739/25 First Floor, Divya Enclave
Off: M.G.Road, Mangalore-575003
Karnataka,INDIA
Phone: 6366052288
