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Foundation on Solid Data Science Course

Home Course Foundation on Solid Data Science Course
Foundation on Solid Data Science Course

Foundation on Solid Data Science Course

Course Duration: 10 Months & 2 Months Intern

Weekly: 2 Days ( 8.00 PM)


Basic knowledge of programming

Laptop/Desktop with Internet Connection

8-10 hours of commitment to learning per week

About HR VENTURE Data Science:

Accelerate your career with Solid Foundation on Data Science course in Bangladesh. This is an International Faculty and all of the trainers are industrial experts on Data Science training.

Data science is a hot topic in recent technologies. So if you update yourself, you must learn data science techniques according to the future of data demand. Concerning other countries recently, data science courses are popular in Bangladesh too.

Data science is an interdisciplinary field. It uses scientific techniques to extract knowledge and insights from structured and unstructured data and apply knowledge and actionable insights from data across a broad range of application domains.

Data Science Training in Bangladesh can learn all domain students, job holders, businessmen, and entrepreneurs. This field is open to all. The basic skills required to learn a data science course in Dhaka are math, statistics, and some programming knowledge.

If you search for a data science training program in Dhaka city, you may find several institutes that give you live training but not a lot of hands-on practice.

If you are interested to learn a Data science course online HR VENTURE is the perfect place here in Bangladesh. We ensure you build your skills strong that helps your self-confidence.

Besides, HR VENTURE also refers to interns after completing the course. And also give opportunities to involve with the international, government and reputed projects, which influences the skills.

HR Venture is a trusted institute for learning  Artificial intelligence courses in Bangladesh.

30% Lectures + 70% Live coding, Exercises, and Demo projects

10 hours of coursework

Mentored Kaggle project participation

Fundamentals of Data Science

Data Exploration, Visualization, and Feature Engineering

Hands-on coding: Data Exploration, Visualization, and Feature Engineering

Machine Learning Fundamentals

Classification Algorithms

Introduction to Predictive Modeling

Decision Tree Learning

Logistic Regression

Hands-On: Building a Classifier

Hands-On Activity: Determining the best split for Classification Models, Evaluation, and Cross-Validation

Regression Algorithms

Linear Regression

Regularized Regression Models

Hands-On Lab: Building a Regression Model

Hands-On Activity: Evaluating Performance, Finding Maxima and Minima, Gradient Descent, Visualizing Features and Parameters

Unsupervised Learning

K-Means Clustering

Hands-On Lab: Using K-Means Clustering

Recommender Systems

Text Analytics

Content-Based and Collaborative Filtering

Evaluation of Recommendation Systems. DCG, nDCG

Hands-On Lab: Analyzing a Document Collection

Hands-On Activity: Using TF-IDF and Cosine Similarity to Query a Document Collection

Operationalizing Machine Learning Models

Metrics and Methods for Evaluating Classification and Regression Models