69999 69999 BDT
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
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
Data Exploration, Visualization, and Feature Engineering
Hands-on coding: Data Exploration, Visualization, and Feature Engineering
Machine Learning Fundamentals
Decision Tree Learning
Hands-On: Building a Classifier
Hands-On Activity: Determining the best split for Classification Models, Evaluation, and Cross-Validation
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
Hands-On Lab: Using K-Means Clustering
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