- Personalized 1 to 1 Interactive Program – 99 $ / Hour
- Online Interactive Training Program
No prior experience required. Open to beginners and professionals interested in learning about machine learning and data science. Basic computer literacy and a strong interest in the field are recommended.
Comprehensive Curriculum
Hands-on Learning
Expert Instructors
Interactive Learning Environment
Flexibility and Convenience
Support and Guidance
Industry-Relevant Skills
Team Academy
Enhanced Knowledge
Skill Development
Career Opportunities
Hands-on Experience
Expert Guidance
Networking Opportunities
Personal Development
Module 1 : Data science professional – Level 1
1.1 Analyze discrete data and structured data using Excel
1.2 Apply descriptive and inferential statistical tools and techniques
1.3 Summarize and represent data visually using graphs, charts, and pivot tables
1.4 Write Python programs to do data analysis using Python libraries such as Pandas, NumPy
Module 2 : Data science professional – Level 2
2.1 Source, validate, clean, store and query data and perform data analysis
2.2 Create data dashboards & visualizations using Tableau
2.3 Slice and dice data to generate hypotheses
2.4 Use statistical tools to validate a hypothesis
2.5 Create data and ML models for business forecasting and predictive analytics
2.6 Apply story-telling techniques using data to engage with stakeholders and help in data-based business decision-making
Module 3 : Data science professional – Level 3
3.1 Modelling data using machine learning tools and techniques
3.2 Analyse unstructured textual data
3.3 Construct, define and validate the ML models for supported / automated decision making
3.4 Use NLP to do analysis on textual data
3.5 Complete a project including ML modelling: Business understanding - Data preparation - Data Analysis - Prepare ML model - Deploy ML Model - Demo & Present Insights
Module 4 : Machine learning
4.1 Learning Introduction
4.2 Supervised Machine Learning
4.3 Unsupervised Machine Learning
4.4 Train Test Split
4.5 Regression Analysis
4.6 Linear Regression
4.7 Logistic Regression
4.8 KNN
4.9 SVM
4.10 Decision Tree
4.11 Random Forest
4.12 K Means Clustering
4.13 GridSearch CV
Q : Who are these courses suitable for?
A: Our courses are suitable for individuals at all skill levels, from beginners with no prior experience in machine learning and data science to professionals looking to enhance their knowledge and skills in the field.
Q : What are the prerequisites for these courses?
A: The prerequisites may vary depending on the specific course. However, basic programming knowledge and a strong interest in the field are recommended. Some advanced courses may have prerequisites such as foundational understanding of mathematics, statistics, or algorithms.
Q : What programming language is used in the courses?
A: Our courses predominantly use Python, which is widely adopted in the machine learning and data science community for its extensive libraries and tools specifically designed for these domains.
Q : How are the courses delivered?
A: The courses are typically delivered through a combination of video lectures, hands-on exercises, coding projects, and assessments. You'll have access to an online learning platform where you can access course materials, submit assignments, and interact with instructors and fellow learners.
Q : Is there any certification provided upon course completion?
A: Yes, upon successful completion of our courses, you'll receive a certificate of completion. This certificate validates your skills and knowledge in machine learning and data science, which can enhance your resume and demonstrate your commitment to professional development.
Q : Can I work at my own pace?
A: Yes, our courses offer flexibility, allowing you to learn at your own pace. While there may be suggested timelines, you'll have access to course materials and lectures that you can engage with according to your availability and preferred learning speed.
Q : Are there any opportunities for hands-on practice and real-world projects?
A: Yes, our courses emphasize hands-on learning. You'll have opportunities to work on practical exercises, coding projects, and real-world case studies. This hands-on approach allows you to apply the learned concepts to real datasets and gain practical experience.
Q : Can I get support and guidance during the course?
A: Absolutely! We provide support and guidance throughout your learning journey. You'll have access to dedicated support channels such as discussion forums, Q&A sessions, and instructor assistance to get your questions answered and receive guidance whenever needed.
Q :Are the course materials accessible after completion?
A: Yes, you'll have continued access to the course materials even after completion. This enables you to revisit the content, review concepts, and refresh your knowledge whenever needed.
Q :How will these courses benefit my career?
A: Completing these courses can open up a range of career opportunities in machine learning and data science. The skills and knowledge acquired will enable you to pursue roles such as data scientist, machine learning engineer, data analyst, or AI researcher in various industries that rely on data-driven decision making.
Our Accolades
View our Verified Achievements & Accolades
Sunday,Monday,Tuesday,Wednesday,Thursday,Friday,Saturday
January,February,March,April,May,June,July,August,September,October,November,December
Not enough items available. Only [max] left.
Add to WishlistBrowse WishlistRemove Wishlist
